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9,914 | https://devpost.com/software/sistema-de-historico-de-pacientes-publicacao | mapa de telas
Desenvolvemos um projeto para área de saúde pública que visa atender a população mais carente. O projeto trata da gerência dos dados históricos de pacientes. A ideia é desenvolver um Data Lake (um repositório de dados estruturados, semi-estruturados e não-estruturados) que armazene os dados dos pacientes. A vantagem do Data Lake é que é possível associar a dados estruturados (um banco de dados existente), dados não estruturados como imagens de um exame, etc. Além de ser possível aplicar técnicas de aprendizado de máquina sobre esses dados. É um ambiente de integração de dados sem todo o custo de bancos de dados multidimensionais como Data Warehouses e Data Marts. A partir desse Data Lake, o plano é desenvolver um sistema que seja capaz de gerenciar/consultar os dados. Resumidamente um banco de dados atualizado, confiável, seguro e gerenciado com dados e informações pelos pacientes e seus médicos. O fato de usar a tecnologia de Data Lake faz com que esse projeto possa ser utilizado em qualquer lugar do mundo da mesma forma. Finalizando podemos usar a saúde pública nos controles de doenças de forma coordenada mundialmente e ajudar diretamente quem mais precisa nos momentos de pandemia além de poder projetar futuros surtos de doenças através de inteligência artificial e modelos de projeção matemáticos.
Built With
data
flutter
Try it out
xd.adobe.com | Sistema de Historico de Pacientes | Leve sua vida consigo onde for! | ['Jose Alexandro Acha Gomes'] | [] | ['data', 'flutter'] | 21 |
9,914 | https://devpost.com/software/covitimas-va7k2t | Precadastro
Serviços
Converseconosco
Menucentral
Cadastro1
Diario2
MenuPaciente
Assistencia
Diario
Familiar
Cadastro4
EsqueciSenha
Cadastro2
Cadastro3
Login
PedidoAssistencia
ObservarPaciente
Orientações
Perfil
Inspiration
Nos inspiramos e nos motivamos com a atual situação de pandemia, que impactou o mundo inteiro. Inspirados pela vontade de ajudar e mudar o atual cenário mostramos juntos que é possível ajudar mesmo em casa. Todos juntos contra o COVID19 esse é nosso espírito.
What it does
Nosso aplicativo fornece um acompanhamento de sintomas para o paciente que testou positivo para a COVID19, onde é possível relatar sintomas diariamente, se informar sobre medidas de prevenção da disseminação do vírus, melhor forma de praticar o isolamento domiciliar, dentre outras informações que serão disponibilizadas
Além disso, quando identificado um agravamento de estado clínico, o paciente pode receber a visita de uma equipe de saúde para avaliação, ou ser indicado para a Unidade mais favorável a atender esse paciente.
Caso paciente e familiares precisem de máscaras , essas serão disponibilizadas por uma equipe do governopor meio de solicitação via appp. Caso o paciente precise de itens de subsistência tais como alimentos e produtos de higiene , o usuário terá a opção de acionar uma equipe de serviço social para providenciar o necessário.
Ou seja ,nosso aplicativo, acima de tudo procura dar ao paciente um atendimento mais humanizado, disponibilizando uma ligação direta com um profissional de saúde, tentando de alguma forma aliviar o peso e o sofrimento em tempos tão difíceis.
How I built it
Trabalhamos em equipe e juntos aprendemos um pouco sobre React e construímos toda a aplicação com o React Native.
Challenges I ran into
Um dos desafios foi que nossa equipe era pequena (3 hackers) e o nosso conhecimento de React é reduzido.
Accomplishments that I'm proud of
Nos orgulhamos do resultado final, pois em 3 dias para aprender, programar e por em prática é um resultado admirável.
What I learned
Aprendemos a trabalhar em equipe a distância e com pessoas novas. Além de aprendermos a usar o React.
What's next for CoVitimas
O que esperamos é que o CoVitimas possa ajudar pessoas que estão num momento tão delicado, e que com patrocinio nós possamos aprimorar o app e implementar todas as funcionalidades que idealizamos.
Built With
react
Try it out
github.com
drive.google.com | CoVitimas | CoVitimas é um aplicaivo que possui o objetivo de ajudar de forma educativa os pacientes positivos para a doença com o isolamento domiciliar e acompanhamento diário dos sintomas. | ['Athena Fernandes Sarantôpoulos', 'Naiara Cristiane', 'Guilherme Jordão'] | [] | ['react'] | 22 |
9,914 | https://devpost.com/software/assistente-comunitario-digital-de-saude-5k1fsn | aulas sobre vírus e coronavírus
localiza caso de crise
mapa pias do bem
movimentos voluntários no território
pias do bem
quais são as dores
mapa com pontos de instituições de urgência e emergência e casos de Covid19 no Brasil
dor para ser resolvida atender o problema antes de chegar ao hospital
Inspiration
Garantir a monitorização e orientação de casos críticos de queixas de saúde durante a pandemia de covid19 para populações de comunidades e vulneráveis.
Garantir cuidados com a população vulnerável durante a pandemia: Comunidades, população de rua e outras.
What it does
Monitoriza queixas de saúde relacionadas com instabilização clinica e registra a evolução do caso com orientação de nível assistencial necessário para o cuidado de forma automatizada.
http://m.me/coracovid19
- assistente comunitário digital de saúde. Alimenta painel de bordo/dashboard de gestão de casos críticos de pacientes com queixas clínicas de comunidades e populações vulneráveis.
Painel de gestão de casos de covid19 em áreas de vulneráveis, rede de apoio e distribuição de água solidária e pias do bem e movimento de voluntários nas comunidades e ações.
How I built it
Plataformas conversacionais e de sistemas de informação geográficas. Painel de bordo gestão da pandemia para comunidades e populações vulneráveis, gestão de rede solidária de apoio a vulneráveis e pias do bem.
Challenges I ran into
Desafio 108, Desafio 115, Desafio 46, desafio 190, desafio 217 e desafio 218.
Accomplishments that I'm proud of
Aplicação de tecnologias e desenvolvimento de conhecimento em SIG, banco de dados,uso de painéis de gestão (dashboard) com captura de dados dos assistentes digitais de saúde com aplicativos de mensagens em telefones celulares. Integração com plataformas conversacionais para captura dos dados. Identificação de dataset para alimentação dos SIG, áreas de comunidades no brasil, unidades hospitalares de urgência, projeto pias do bem que entrega água para população vulnerável se proteger higiene e limpeza da mão. identificação de camadas de mapa (aglomerados anormais, casos de covid19 brasil, unidades de pronto atendimento brasil, locais de instalação das pias do bem, locais de ativação do assistente comunitário digital de saúde dentre outros).
What I learned
Como criar painéis de bordo dashboard para gestão de programas relacionadas com a crise da pandemia de covid19, Interação com mentores.
Identificação e mapeamento geográfico de vulneráveis nos territórios. Usar base dados do ibge, bases geomapas de repositórios na internet.
What's next for Assistente Comunitário Digital de Saúde
Seguir como um serviço e produto para validação de campo em comunidades, identificar campo para aplicação de testes de validação do serviço ou produto. Criar chatbot para gestão de ações de vulneráveis nos territórios(exemplo:crises de saúde, pias do bem, movimento de voluntários em comunidades).
Built With
analytics
artificial
banco
chatbot
cloud
dados
geografica
gis
google
informacao
inteligencia
nip
sig
sistema
tecnologia
Try it out
hhrobots.maps.arcgis.com
m.me
arcg.is | Assistente Comunitário Digital de Saúde e Ações Voluntárias | Projeto Hackaton Covid-19 - Solução Monitorização remota de casos ou suspeitas de Covid-19 e Sistema de Informação Geográfica para vigilância em saúde de comunidades e populações vulneráveis | ['Éderson Almeida Pedro', 'Leticia Luísa', 'Karla Susiane dos Santos Pereira', 'Nathalia Fernandes', 'Marcio Pessoa', 'Vandoir Welchen'] | [] | ['analytics', 'artificial', 'banco', 'chatbot', 'cloud', 'dados', 'geografica', 'gis', 'google', 'informacao', 'inteligencia', 'nip', 'sig', 'sistema', 'tecnologia'] | 23 |
9,914 | https://devpost.com/software/simcco-simulador-de-medidas-contra-covid-19 |
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Nome do projeto:
SIMCCO – Simulador de Medidas Contra Covid-19
Descrição resumida do mesmo:
Membros da equipe que desenvolveram o projeto:
Ana Carolina de Carvalho – proposta e coordenação de projeto, conteúdo científico
Erick Garcia Terra – coordenação de projeto, programação, game design
Jhonas Mutton – programação
Alisson Meneghello – design gráfico
Victor Frazatto – sonoplastia
Alexandre Borin – conteúdo científico saúde
Isabella Capistrano – conteúdo científico comunicação
Lucas Zillig – conteúdo científico saúde
Ana Carolina Vilela de Lima– conteúdo científico economia
Sua inspiração (Inspiration);
Jogos: Plague Inc., Reigns, This is the police, Bio Inc.
Artigos científicos e jornalísticos com projeções sobre crescimento da covid-19 e seus impactos.
Trabalhos de instituições, coletivos e comunidades para combater a pandemia e proteger a população.
O que faz o projeto (What it does):
O jogo para smartphone SIMCCO traz o jogador para o papel de um gestor público que precisa adotar estratégias para combate da pandemia de covid-19. Tomando decisões relacionadas a Saúde, Economia e Comunicação, ele deve proteger sua região e seus habitantes dos impactos negativos da pandemia. Através de uma mecânica de estratégia por turnos, o jogador receberá repasses de uma instância superior de governo e terá de destinar a verba escolhendo dentre diversas estratégias de enfrentamento à pandemia dentro das áreas disponíveis, e então ver como esta alocação de recursos e aplicação de estratégias impacta - positiva ou negativamente - o número de novos casos da doença e de mortes em decorrência da mesma. O objetivo é de sobreviver com a maioria da população viva, sem superlotar o sistema de saúde e sem reduzir a satisfação da população. A cada turno, pop-ups no formato de notícias explicarão ao jogador como aquelas medidas adotadas impactaram a população, e neste momento são veiculadas as informações que buscam conscientizar os jogadores sobre
Como fizeram (How I built it);
Utilizando Unity, Android SDK, C# e Json
Dificuldades que encontraram (Challenges I ran into);
Simplificar os cálculos de projeção de casos e o conteúdo dos cartões, sem perder a função informativa. Balancear as mecânicas de jogo. Resolver aspectos pontuais de programação.
Transformar modelos matemáticos em funções de um jogo que simule ao máximo a realidade do Covid-19
Realizações das quais nos orgulhamos (Accomplishments that I'm proud of);
O jogo todo, praticamente. O visual é simples, funcional e bonito; as músicas criam a atmosfera do jogo e adicionam à experiência, transitando entre momentos de calma e foco até tensão e senso de urgência; o conteúdo científico está diverso e aborda uma série de aspectos importantes que muitas vezes não são discutidos, como o impacto da comunicação no desenvolvimento da pandemia, a realidade de comunidades periféricas e como tem sido o trabalho realizado com e por elas para enfrentamento da situação nas parcelas mais vulneráveis da sociedade, a relação entre saúde e trabalho e afins. A equipe de programação atravessou diversos desafios e foi capaz de entregar um protótipo funcional em tempo recorde; estamos muito satisfeitos com o andamento do projeto e a comunicação entre a equipe.
O que aprendemos (What I learned);
Configurar scrollbar no unity, balancear mecânicas de jogo, novas informações acerca das estratégias de enfrentamento da covid-19 pelo mundo.
Próximos passos (What's next for your project);
O protótipo apresentado aqui é somente uma fração da ideia do jogo, simplificada para fins de demonstração dentro do espaço de tempo para desenvolvimento do projeto dentro do hackaton hackcovid-19. Se possível, pretendemos futuramente ampliar as mecânicas de jogo, melhorando o balanceamento das mesmas, inserindo diferentes níveis de dificuldade para escolha do jogador, aparecimento de eventos aleatórios interferindo nos índices do jogo e introduzindo maior aleatoriedade e desafios. Novas páginas detalhando os índices que o jogador deve acompanhar também são uma adição desejável: as informações separadas de casos sintomáticos e assintomáticos, casos graves, coeficientes de incidência e mortalidade e afins estão disponíveis somente para fins de cálculo no sistema do jogo, não ficando visíveis para o jogador.
Built With
.netframework
c#
json
unity
Try it out
drive.google.com | SIMCCO – Simulador de Medidas Contra Covid-19 | Você é um governante que precisa escolher as estratégias certas para proteger seu povo da covid-19. Será que conseguirá obter sucesso ao longo da sua gestão das políticas públicas? | ['Ana Carolina Vilela de Lima', 'erickterra Garcia Terra', 'Ana Carolina De Carvalho', 'Alisson Meneghello', 'Isabella Capistrano', 'Luccas Zillig', 'Alexandre Borin', 'Jhonas Mutton', 'Victor Augusto Nithack Frazatto'] | [] | ['.netframework', 'c#', 'json', 'unity'] | 24 |
9,914 | https://devpost.com/software/volp | HACKCOVID19 - Desafio 094
github:
https://github.com/leordev/hackcovid19-volp
https://volp-4d850.web.app/
Passos para testar a aplicação:
Acesse:
https://volp-4d850.web.app/
Procure pelo endereço Avenida Maracanã, Tijuca, Rio de Janeiro (nossas ONGs foram cadastradas nessa região apenas).
Crie um pedido de ajuda
Tente se registrar como ajudante e visualizar e atender pedidos de ajudas
https://youtu.be/FPxED8I6tM8
https://devpost.com/software/volp
Proposta do Desafio 094: CONECTAR PESSOAS E INSTITUIÇÕES DE CARIDADE
Nesse momento muitas pessoas em situação informal de trabalho precisam de assistência. Os governos estão a garantir parcialmente isso, porém o valor pode não ser suficiente. Além disso há atrasos, filas e complicações. Existem diversas instituições de caridade, sejam ongs ou sejam igrejas, promovendo campanhas nas redes sociais tentando compartilhar ao máximo de pessoas possíveis. Seria interessante algum tipo de aplicativo onde pessoas interessadas em doar se cadastrassem e instituições que já realizam o trabalho também, para conectar. Seja por tags do tipo de ajuda, seja geograficamente. Com ajuda material, financeira ou voluntariando fisicamente. Essas instituições não tem fundos para promover nas redes sociais.
proposta enviada por Guilherme Vieira de Abreu e Silva
Inspiração
Em tempos de pandemia do COVID-19 vimos muitas pessoas passando necessidade e muitas pessoas querendo ajudar. Por isso pensamos em alguma forma de conectar essas pessoas
What it does
Instituições de caridade podem se vincular a nossa plataforma e promover suas informações e serviços para que consigam ajudar ainda mais pessoas necessitadas.
Além disso, pessoas carentes ou pessoas (principalmente as de risco) na quarentena pelo COVID-19 podem solicitar ajuda para que os ajudantes possam verificar sua solicitação e aceitar a mesma. A solicitação de ajuda pode ser remunerada ou doada.
How we built it
Nós criamos uma PWA (progress Web App) em Angular 9, com um backend em Node Express e Typescript, uma base em Postgres, push notifications com Firebase e Geolocalização usando open street maps (OSM Apis) e verificação de código SMS usando a API do Twilio
Challenges we ran into
Nossa plataforma possui diversas funcionalidades e interações. Logo, construir esse sistema em 3 dias foi bem desafiador.
Criação de diversas regras para que o usuário não envie serviços sem a real necessidade (abusando dos recursos e do ecossistema colaborativo que a plataforma oferece).
Accomplishments that we're proud of
Através de um exemplo de trabalho em equipe e ajuda entre os hackers conseguimos entregar um mínimo produto viável incrível para se validado no mercado.
What we learned
Aprendemos a trabalhar com um cronograma muito curto e um escopo grande. Grandes desafios na criação, automatização do mapa e criação de notificações push para comunição entre ajudantes e ajudados.
What's next for VOLP
Um sistema administrador para validar as ONGs fazendo com que todas as informações do sistema sejam autênticas.
Um sistema administrador que vai gerenciar todas as ONGs cadastradas e dar o suporte necessário para a sua projeção.
Os usuários cadastrados poderão registrar incidentes, efeito WAZE. Esses incidentes são: exibir áreas de grande aglomeração, mercados sem suprimentos, upas lotadas e muitos outros.
As ONGs poderão criar campanhas para conseguir as ajudas sobre as atividades que necessita.
As ONGs poderão adicionar ajudantes próprios, dessa forma podemos verificar que as ONGs estão efetuando um trabalho de forma efetiva para ajudar sua comunidade.
Cada pessoa que contribuir dentro da plataforma será avaliado de acordo com o serviço feito e poderá avaliar a ONG para qual fez o serviço.
Built With
angular.js
firebase
gps
heroku
node.js
openstreetmap
postgresql
pwa
twilio
typescript
Try it out
volp-4d850.web.app
github.com | VOLP | A nova forma de Ajudar e ser Ajudado em Tempos de Crise | ['Gabriel Vaz', 'Leo Ribeiro', 'Philipe Lopes'] | [] | ['angular.js', 'firebase', 'gps', 'heroku', 'node.js', 'openstreetmap', 'postgresql', 'pwa', 'twilio', 'typescript'] | 25 |
9,914 | https://devpost.com/software/upa-perto | GIF
mobile-web
web
Sua inspiração
Uma reportagem na TV mostrou uma ambulância que, ao socorrer uma pessoa com síndrome respiratória grave (suspeita de COVID-19), chegou à UPA mais próxima e não havia leito disponíve. Iniciou uma luta na busca de outra unidade para o atendimento, agravando a situação e despendendo um alto tempo e recursos no atendimento.
O que faz o projeto
Como protótipo o projeto visa otimizar o atendimento das equipes de socorro, acelerando o encaminhamento e busca de unidades próximas disponíveis. Tudo de forma visual e intuitiva no mapa, além de outras informações sobre a unidade desejada.
As informações são coletadas da página do Governo do Estado do Espírito Santo, tratadas e normalizadas para serem consolidadas e exibidas no mapa, o qual possibilita a seleção e visualização da localidade das unidades, suas informações e leitos disponíveis para atendimento.
Como fizeram
O projeto é dividido em duas partes:
Back-end: faz um web scraping das informações disponíveis em
https://coronavirus.es.gov.br/leitos-hospitais
e que são atualizadas pelo Estado do Espírito Santo, possuindo informações das unidades/hospitais e leitos (UTI e Enfermaria). Desenvolvido em Python e utilizando conceitos de data mining é facilmente integrável às tecnologias cloud para execução just-in-time;
Front-end: consolida e disponibiliza as informações de forma intuitiva para a identificação da unidade, localização, disponibilidade, entre outras. Feita em formato web app utilizando o módulo de mapas de código aberto Leaflet e hospedado no Firebase Hosting, acessível pelo navegador e adaptável ao dispositivo do usuário, seja um desktop ou um smartphone. Tudo desenvolvido com frameworks de código aberto.
Dificuldades que encontraram
O formato de publicação dos dados pelo Governo do Estado do Espírito Santo dificultou o web scraping, assim como cada Estado possui sua formatação e formas diferentes de publicação, trazendo para o projeto um alto grau de complexidade no data mining.
A ideia inicial para ter os dados de leitos disponíveis atualizados em tempo-real era na hora do atendimento o sistema disparar uma ligação telefônica automática (semelhantes às URAs) para consultar as Unidades de Atendimento da quantidade de leitos disponíveis, tudo de forma automatizada, mas com necessidade de intervenção por parte da Unidade que atenderia ao telefone. Para grandes capitais a PoC se tornou insustentável devido à possibilidade de alto índice de ligações às Unidades de Atendimentos.
Uma possibilidade de melhoria seria a unificação das informações de leitos disponibilidades das unidades dos Estados pela OMS (ou algum Órgão Federal), resultando em normalização dos dados e consulta em uma fonte única de informação.
Realizações das quais nos orgulhamos
Em um tempo relativamente curto conseguimos desenvolver o sistema e a interface para demonstrar a viabilidade da ideia proposta e, além de tudo, possibilitar ajudar na otimização dos recursos no tempo tão difícil e caótico que estamos enfrentando.
O que aprendemos
Que conseguimos produzir muito remotamente mesmo com distanciamento e que não precisa de muito para termos ideias criativas e que podem trazer grandes benefícios. E o principal, que existem muitas pessoas dispostas a ajudar, que foi o caso dos mentores! Estão de parabéns!!
Próximos passos
Avaliar novas fontes de dados;
Integrar com mais Estados e Unidades de Atendimento;
Avaliar soluções cloud;
Disponibilizar processo de web scraping em cloud para se tornar auto-escalável;
Built With
bootstrap
firebase
javascript
jquery
leaflet.js
python
Try it out
upa-perto.web.app | UPA Perto | O projeto visa otimizar o atendimento das equipes de socorro, acelerando o encaminhamento e busca de unidades próximas com leitos disponíveis. | ['Dirceu Pauka Junior', 'Bruno Heins'] | [] | ['bootstrap', 'firebase', 'javascript', 'jquery', 'leaflet.js', 'python'] | 26 |
9,914 | https://devpost.com/software/governativa | O que é Governativa?
Governativa é um aplicativo de workflow ecosystem de apoio ao cultivo e ao cuidado com fitoterápicos desde a produção até a sua distribuição comercial usando blockchain para garantir qualidade ISO de informações e produtos; aplica-se também como uma sala de situação farmacoepidemio e farmacovigil que incorpora boas práticas de manejo agroecológico e clínico de fitoterápicos.
Os fitoterápicos em questão são espécies presentes no território brasileiro já apontadas em estudos científicos dentro do contexto da pandemia, e podem ser consumidos e utilizados pela população em terapias profiláticas e paliativas na busca de evitar possíveis sintomas severos ou morte pelo COVID-19. Sendo assim, é destinado a atender grupos de todos os segmentos sociais: comunidades vulneráveis, ONGs, empresas locais, governo; e especialmente aos assistentes de saúde rurais, agentes comunitários de saúde e técnicos, além outros grupos que sejam catalisadores de ações neste tema.
Como ela funciona?
Os dados coletados pelo app através de georreferenciamento, formulários e questionários orientam a visita de agentes de saúde, agentes de inspeção sanitária, e técnicos de áreas associadas até o domicilio, cooperativas locais ou empresas de fabricação de produtos naturais.
Desta maneira, cada vez que uma etapa do processo produtivo ou de manejo for executada, a base do blockchain é atualizada e validada. Alimentando o banco de dados e estabelecendo um plano diretor de protocolo nas comunicações sobre o tema.
O trabalho colaborativo entre ATER e ESF dão suporte às várias fases da integração entre recursos de trabalho disponível.
Qual o diferencial de Governativa?
Apontamos aqui um aporte telemático para uma governança descentralizada.
Descrevemos um Cloud Flow Design que suporte um repertório, um memento fitoterápico, considerando o saber popular no estabelecimento duma sala de situação farmacoepidemio e farmacovigil; um sistema de garantia que incorpore as boas práticas de manejo e administração de fitoterápicos associados.
Há ainda,contempla uma integração de funcionalidade de aplicações mobiles (Play Store), complementos para plataformas nas nuvens (G Suite Marketplace) e suplementos para navegadores (Chrome Webstore); um desenho que, partindo do Padrão de Registro de Metadados ISO/IEC 11179, instrumente a inspeção sanitária interpares e a emissão de laudos de qualidade.
Propomos um workflow, um cloud flow baseado na G Suíte e em arquiteturas de Distributed Ledger Technology para automação de processos e validações governamentais no âmbito do cultivo de e do cuidado com fiteterapicos. São eles: São eles: 4 aplicativos para a plataforma android:
Insightly CRM (Insightly Inc.), Leitor de QR Code (TWMobile), Authy 2-Factor Authentication (Authy) e Ethereum Block Explorer (ApprovedApps); 4 suplementos para Google Forms: Ultradox (loreysoft), Data Director (AJ Add-ons), Form Builder (Jivrus Technologies) e Email Notifications for Google Forms (Amit Agarwal); 3 complemento para Gmail: Insightly CRM Sidebar (Insightly Inc.), Free Email Tracking for Gmail (Mailtrack) e Smartsheet for Gmail Add-On (Smartsheet); e 8 complementos para Google Sheets: KPIBees - Import API, MySQL, Google Analytics (KPIBees), Export Sheet Data (Chris Ingerson), Drive Explorer - Google Drive on Sheet (Ganapathy S), QR Code Generator (INNOVA apps), Blockchain For Sheet (Squadx), Form Builder for Sheets e Sheet Director (Jivrus Technologies), Save Emails and Attachments (Amit Agarwal).
Nossas principais referências são os aplicativos da ATER Atividades, e-SUS AB Território, e-SUS AB Atividade Coletiva e MedSUS.
Try it out
gg.gg | Governativa | Ecossistema de fluxo de trabalho (workflow) para criação e uso de índices de participação social e governança no contexto de fitoterápicos cujas propriedades possuem ação anti-COVID-19. | ['Metateca Inc', 'Irvyn Ricardo'] | [] | [] | 27 |
9,914 | https://devpost.com/software/vox-of-life-y6ld4o | Inspiration:
Inspired to come up with a solution for social isolation during this time! We need social interaction and we need people to talk to!
What it does:
We connect new people on spontaneous, meaningful, voice-first interactions, to get people talking!
How I built it:
We used non-code tools such as Airtable and Zapier to automate the workflow. We have a fully autonomous code-based solution ready for large scale development.
Accomplishments that I'm proud of:
Over 30 meaningful interactions.
What I learned:
Spontaneous interactions can be powerful to improve someone's outlook.
What's next for Vox of Life:
We are looking to do a public beta, if you would like to give it a try, please visit voxoflife.com. Thank you! | Vox of Life | #voxoflife We are helping people deal with social isolation. We connect new people on spontaneous, meaningful, voice-first interactions. | ['Shiv Soneja'] | [] | [] | 28 |
9,914 | https://devpost.com/software/receita_digital | Inspiração
O projeto Receita Digital nasceu em maio de 2020, durante a pandemia mundial de COVID-19.
Com o coronavírus e a quaretena, a realidade dos brasileiros, assim como de todo o resto do mundo, mudou abruptamente. Atividades do dia a dia tidas como certas passaram a representar riscos e, com entes queridos distantes e às incontavéis notícias devastadoras relatadas na TV, elas também passaram a representar uma grande fonte de ansiedade. Nesse contexto, o Receita Digital surge para aliviar, mesmo que apenas um pouco, a carga de estresse desse período.
A história começa com o atividor do projeto, Igor. Realizando o uso contínuo de medicamentos, ele não pode contactar seu médico para pegar a receita usual, pois o último encontrava-se infectado pelo coronavírus. Assim, o objetivo da aplicação é ajudar os Igor's, Joãos, Marias e Anas pelo mundo que precisam obter seus medicamentos, mas não podem.
O que nossa solução faz
A nossa solução consiste em um sistema web responsivo que permite permite ao paciente renovar sua receita sem precisar ir ao médico e obter seus medicamento sem precisar ir à farmácia. O sistema facilita e centraliza a emissão, a autenticação e o "uso" de receitas médicas. Ele abstrai toda a emissão e a autenticação, validando essas receitas digitalmente. Além disso, possui uma interface para que o paciente visualize suas receitas e tenha controle do seu histório. O mesmo vale para os médicos!
Como nós a construímos
A construção da ferramenta se deu em cima do framework python Django para o back-end e do Bootstrap 4 para o front-end. Inicialmente, esboçamos juntos uma ideia do que seria necessário ao nosso sistema, e a evoluímos por meio de feedbacks e análises feitas por meio de um formulário.
Desafios que encontramos
O maior desafio que encontramos foi em relação a autenticação. Precisávamos de uma maneira segura de garantir a validade da receita, tal qual feito pelo ITI/ICP-Brasil. Dentro do período do hackaton, não conseguimos realizar a integração a esse sistema, mas bolamos uma solução engenhosa para autenticar as prescrições médicas.
Outros desafios dizem respeito a falta de conhecimento do meio no qual a solução foi desenvolvida. Com mais apoio de médicos, farmárcia e pacientes, seriam capazes de capturar suas necessidades e desenvolver uma solução mais completa.
O que aprendemos
Aprendemos muito a respeito de autenticação digital, desenvolvimento de sistemas web, integração de banco de dados, desenvolvimento de telas e muito muito mais. Aprendemos sobre as dificuldades que todo mundo enfrenta e aprendemos, também, o quanto é importante escutá-las.
O que vem a seguir para o Receita Digital
1) Verificação, por parte do paciente, de que aquele medicamento foi realmente comprado.
2) Limitador na quantidade de receitas emitidas digitalmente:
3) Necessidade de atendimentos presenciais para acompanhamento.
4) Possibilidade de extensão para um app.
5) Possibilidade de adicionar requisição de exames.
6) Integração com o sistema do ITI/ICP-Brasil.
7) Integração com outros bancos de dados.
Muito obrigado por nos acompanhar até aqui!!
O nosso pitch se encontra no vídeo do youtube! Os slides também estão disponibilizados.
Built With
bootstrap
django
html
javascript
makefile
python
scss
Try it out
github.com
docs.google.com | Receita Digital | Receita Digital - Projeto relacionado ao Desafio 002 do Hackcovid 19. | ['Ariel Ribeiro', 'Hugo Davila', 'Marco Diniz Sousa', 'Daiane Henrique', 'Marcelo Hoffman Barros', 'Gabriela Ramalho'] | [] | ['bootstrap', 'django', 'html', 'javascript', 'makefile', 'python', 'scss'] | 29 |
9,914 | https://devpost.com/software/checknews | Ícone do Fareja Fatos
Fareja Fatos pronta para receber a notícia a ser analisada
Inserindo uma notícia para análise no Fareja Fatos
Resultado da análise do Fareja Fatos para uma notícia verdadeira
Nossa inspiração
A principal motivação do grupo para participar do evento foi buscar formas de contribuir para a mitigação dos efeitos adversos da pandemia do novo coronavírus. Diante dos 213 desafios propostos, decidimos desenvolver um detector de fake news, conforme proposto por vários ativadores.
Na atual conjuntura, percebe-se um número alto de notícias, muitas vezes erradas, sendo divulgadas principalmente pelas redes sociais o que, infelizmente, contribui negativamente para vida de muitas pessoas.
Considerando as características daqueles que mais disseminam fake news, tem-se que usuários acima dos 65 anos compartilham até sete vezes mais artigos de portais de notícias falsas do que o grupo etário mais jovem.
Comparando a pandemia da COVID-19 com a gripe espanhola, a cólera, a peste negra e demais, é visto que uma das maiores vantagens atuais é a eficiência das nossas interações e comunicações uns com os outros, o que não era possível anteriormente.
Graças a divulgação de medidas preventivas de saúde e de higienização foi possível diminuir, e muito, o número de óbitos que poderia ser esperado.
Ao levar em consideração os séculos passados, conclui-se, portanto, que a divulgação de informações corretas pode salvar vidas.
Com essas ideias em mente, é deveras importante a existência de um filtro para notícias falsas, denominadas fake news, pois estas acarretam em resultados antagônicos às true news.
O quê o projeto faz
O app Fareja fatos:
(I) tem como funcionalidade principal a análise de informações, indicando a probabilidade da informação ser verdadeira. As informações devem estar no formato texto, na língua portuguesa e o app requer acesso à internet.
(II) sugere notícias relacionadas à informação analisada a fim de que o usuário possa avaliar fatos relacionados e, assim, instiga a análise crítica e a formação da própria opinião. Dessa forma, respeita-se a autonomia do usuário e cria-se um contexto favorável à educação do mesmo, com vistas à diminuição da propagação de notícias falsas.
(III) conta com o apoio de um tutor-personagem (denominado como Farejadog) para apresentar os resultados da análise, auxiliar no uso da ferramenta e interagir com o usuário tendo como foco proporcionar maior acessibilidade para o público-alvo da solução.
(IV) se apresenta como um dos apps da lista de compartilhar informação e, se selecionado, encaminha o texto diretamente ao app para ser analisado. Desse modo, diminui a quantidade de ações necessárias para usar o app, facilitando o uso por pessoas idosas.
(V) bot (robô) no app WhatsApp que ao receber o texto para ser analisado, devolve o resultado no próprio WhatsApp. Essa funcionalidade facilita o uso de quem possui internet limitada, mas com acesso ao WhatsApp.
Como fizemos
O aplicativo foi criado utilizando o framework Flutter com a linguagem Dart.
Ele se comunica com a API enviando a amostra inserida pelo usuário através de requisições HTTP.
A API foi criada em Python, usando o framework Flask para o gerenciamento das rotas. Ela processa a requisição e passa essa amostra por um classificador.
A notícia enviada para classificação passa por um pré processamento que a transforma em uma matriz numérica esparsa segundo o algoritmo Term Frequency-Inverse Document Frequency (TF-IDF), que confere pesos às palavras dependendo da frequência em cada documento e no córpus inteiro.
Os atributos extraídos do texto são então passados a um Voting Classifier composto por um algoritmo Random Forest e um Support Vector Machine, com pesos de votação iguais. Com isso a notícia pode ser classificada automaticamente como falsa ou verdadeira baseada na probabilidade calculada pelo classificador. Todos os algoritmos foram criados usando o pacote scikit-learn em Python.
O córpus usado para treinar o algoritmo de classificação foi o Fake.Br, com 7200 notícias divididas igualmente entre verdadeiras e falsas.
Em seguida são identificadas palavras chaves dentro da amostra e elas são usadas como parâmetro de busca por notícias relacionadas na API do Google News. Essa API retorna os links e títulos das matérias que são usados como entrada para um script que coleta a respectiva imagem.
Esse link, imagem e título são retornados juntos ao resultado do classificador para o aplicativo que os exibe.
Dificuldades
Entre as dificuldades encontradas destacamos: a seleção do desafio, a hospedagem e configuração da API em um serviço de cloud seguro e acessível, a integração da aplicação com o WhatsApp, a definição do que seriam as fake news e as implicações legais de suas exibições, a expansão do córpus de notícias, a integração com um serviço agregador de notícias confiáveis, a criação de um mascote e slogan, e a definição da interface do app.
Realizações das quais nos orgulhamos
Nos orgulhamos do trabalho em equipe que foi eficaz, eficiente e harmonioso, apesar da equipe, formada majoritariamente por pessoas de diferentes áreas e que não se conheciam, ter atuado num curto espaço de tempo. Além disso, nós prezamos pela gestão participativa e organização dos processos do projeto. Por fim, o aplicativo produzido obteve boa performance nos testes iniciais e, portanto, tem grandes chances de se mostrar eficaz no combate à propagação de fake news.
O que aprendemos
Aprendemos que a realização de um projeto depende dos esforços e motivações coletivas e adequamo-nos a uma nova forma de produzir. Em tempos de pandemia, aderimos ao teletrabalho para conseguir concluir o desafio e atender ao curto prazo de tempo.
Próximos passos para o "Fareja Fatos"
Planejar estratégias de marketing para o público-alvo; atrair investidores; criar meios para o sustento financeiro do app, mantendo a gratuidade para os usuários; criação de funcionalidades para maior acessibilidade do público idoso; expandir os formatos de informações aceitos para análise, como formato imagem e áudio; expandir a base de dados de treino, incluindo uma quantidade maior de notícias relacionadas ao COVID-19; Adotar serviços completos de host para o backend e da API que faz a ligação com o WhatsApp a fim de aprimorar o desempenho e segurança do aplicativo;
Built With
dart
flask
flutter
google-news
machine-learning
python
random-forest
sckit-learn
tf-idf
voting-classifier
Try it out
drive.google.com
github.com | Fareja fatos: o seu farejador de notícias falsas | Desenvolvemos, para combater as fake news, o aplicativo Fareja fatos. O app analisa a veracidade de notícias e tem como público alvo os idosos, proporcionando a estes maior acessibilidade e instrução. | ['Henrique Coutinho', 'Matheus Sales', 'Ana Beatriz', 'Bernardo Fraga', 'João Armando', 'Leilane França', 'Jhonatan Maia Rios'] | [] | ['dart', 'flask', 'flutter', 'google-news', 'machine-learning', 'python', 'random-forest', 'sckit-learn', 'tf-idf', 'voting-classifier'] | 30 |
9,914 | https://devpost.com/software/gis-gestao-integrada-de-saude | Inspiration
Gestantes, idosos, cardíacos e familiares de pacientes já internados e os recuperados da infecção por Covid-19 têm necessidade de manter acompanhamento e monitoramento do seu estado de saúde e ao mesmo tempo manter o isolamento por serem grupos de risco de contágio ou transmissão.
Aplicativos que dão suporte remoto ao paciente poderiam ter sua funcionalidade aumentada através do acesso a uma maior amplitude de dados do paciente .
Funções de monitoramento, registro, assistência e aos pacientes disponíveis um único aplicativo possibilitaria a gestão remota, segura e integrada da assistência aos pacientes
O que nos propomos resolver:
Permitir que a população (pacientes) possam fazer acompanhamento de casos através de aplicativo.
Ter acesso em 1 só aplicativo a todas as funcionalidades já disponibilizadas por outros sistemas do governo
What it does
Como será utilizado inicialmente:
O primeiro grande passo do aplicativo será acompanhar acompanhar casos (COVID-19 e outras doenças)
O aplicativo indicará tomadas de decisão para o paciente de acordo com o estágio de gravidade de seus sintomas
Listagem de postos de saúde mais próximos
How I built it
Através da Integração dos sistemas já existentes e utilizados pelo SUS que possuem histórico dos pacientes.
PEP (Prontuário Eletrônico de Pacientes)
SIPNI (Sistema de Integração do Programa Nacional de Imunização)
O API dos sistemas existentes possibilitam a leitura de dados, mas não permitem que a pacientes incluam dados serem acompanhados pelo seus postos de saúde, porém não configura uma desvantagem ao nosso App, já que o mesmo será uma extensão do que já existe em vários apps do governo e ampliará com a funcionalidade de criar diversos outros registrosO desenvolvimento de uma das aplicações desta solução passa pela integração do banco de dados do PEC com aplicativos utilizando o sistema API .
O desenvolvimento do aplicativo conta com duas funcionalidades :
-Monitorando do estado de saúde dos familiares em quarentena (nesse caso a informação imputada pelo paciente será armazenada em banco de dados do servidor)
Realizar o atendimento remoto dos pacientes do grupo de risco .
Diferencial do app:
Diminuir a necessidade de visitas a postos de saúde/hospitais
Permitir acompanhamento a distância entre agende de saúde e paciente
Challenges I ran into
Desenvolver soluções tecnológicas em um curto período de tempo
Desafio de direcionar o desenvolvimento da tecnologia com objetivo de obter um produto de relevância para sociedade
Desafio de se manter focado na solução do problema de forma concensual
Trabalhar num desafio tendo como cliente uma área que não conhecemos as particularidades e a angústia de desejando fazer o melhor por ela .
Ausência de conhecimentos na área da programação
Estar numa equipe sem programador
Uso de plataformas para o trabalho com as quais não estava habituada
Pouco tempo para entender o que era o Hackaton , seus critérios e ritmo
Pouco tempo para assistir todas as palestra e tutoriais
Equipamentos de casa ocupados com uso dos familiares no home office
Conciliar os trabalhos com as demandas de familiares
Accomplishments that I'm proud of
What I learned
What's next for GIS - Gestão Integrada de Saúde
O que precisamos:
Incentivo para contratar desenvolvedores e investir em mídia para o aplicativo
Como será divulgado:
Inicialmente será um aplicativo não-oficial para que tenha mais rápida aderêncvia de usuários
Faremos um trabalho de campo 1 a 1 contactando agentes de saúde e recomendando que comecem a utilizá-los cara acompanhamento dos pacientes com COVID-19
Evolução futura do app:
Para que o aplicativo seja utilizado pela população o mais rápido possível, faremos evoluções em etapas.
-Próximas etapas:
-Integrar hospital com os familiares de pacientes internados dando suporte como informações remotas sobre a evolução do caso
-Integração com sistema de carteirinha de gestante
carteira de vacinação on line
-Gestão integrada de EPIs
Built With
api
canva
Try it out
www.canva.com | GIS - Gestão Integrada de Saúde | App que integra diversos banco de dados, beneficiando profissionais de saúde, paciente e familiares dos paciente. | ['Katia Reis', 'Giulia Maria', 'Teresinha de Jesus Bittar'] | [] | ['api', 'canva'] | 31 |
9,914 | https://devpost.com/software/ory-z96l7e | Exemplo de combinação de peças
Esquema de peças para recorte
Visualização da POC atual
Inspiração
Inspirado no Osmo :
OSMOCODING
Como funciona
A cada nível, um desafio é proposto. Por exemplo, fazer o personagem chegar na bandeirinha vermelha.
As crianças deverão montar uma sequência de peças para fazer seu robô chegar na bandeira conforme a imagem abaixo.
As peças (start, andar, pular, pegar, esquerda, direita, cima, baixo, 1,2,3,4… etc) podem ser impressas em papel, papel magnético ou EVA na própria
escola
ou
em casa
.
![Peças(]
https://github.com/OryGames/Ory/raw/master/res/image2.png
)
Qualquer um poderá baixar o software
(open source)
, recortar as peças e colocar as crianças para brincar.
As peças poderão ser criadas pelos professores com os mais variados desafios e novas peças poderão ser adicionadas conforme a evolução do projeto.
Capture com a câmera a solução de cada criança a ser executada para ver se ela acertou o desafio.
Então o personagem no jogo realizará as ações programadas pela sequência de peças como a criança montou.
Como foi construído
Basicamente utilizamos
Deep Learning
para fazer o computador entender a imagem dos bloquinhos que as crianças devem montar e simulamos os movimentos com o player em um ambiente lúdico.
Próximos desafios
Criar uma equipe de artistas ( músicos, desenhistas, designers..) junto com os professores para criar os desafios e dar os treinamentos para as comunidades e escolas.
Realizações das quais me orgulho
Como usamos Inteligência Artificial para reconhecer os bloquinhos, estes poderão ser dos mais variados temas: Ecologia, Combate ao Vírus, Saneamento, Higiene, Matemática, Química, etc. o que possibilita o uso para as mais diversas idades.
Não exige um tablet ou computador por aluno basta o celular da professora. Se o aluno tiver um celular ele mesmo poderá testar o seu programa.
É um projeto
sem fins lucrativos de código aberto
disponível no GitHub
Ory Games
O que eu aprendi
O uso de IA para identificação das peças com TensorFlow.
O processo consiste em gerar
milhares de imagens com as peças inventadas
e anotar cada uma delas dizendo o que ela é ( pular, andar, pegar, loop, números 1,2,3, etc... ).
*** Click aqui para ver como o Ory aprende
Ao término das anotações é feito o treinamento para ensinar o computador a reconhecer uma peça dentro de qualquer desafio. (Deep Learnig)
Próximos passos para o OryGames - Jogos Educativos
Conseguir apoio de Universidades, Colégios, Instituições Financeiras, ONGs ou o público em geral que poderão fazer suas contribuições diretamente no código-fonte que é público e aberto.
Try it out
github.com | Ory | Ory é um jogo educativo de código aberto, para introduzir lógica de programação para crianças utilizando um ambiente lúdico e uma linguagem baseada em blocos físicos de encaixar. | ['Rafael Kazuo Sato Simião'] | [] | [] | 32 |
9,914 | https://devpost.com/software/assis | Marca
ChatBot
Dashboard
Equipe
NPS - MVP
Investimento
Inspiration
Servir as pessoas e direcioná-las em um momento de incerteza. Não ficar apenas olhando toda a situação, mas executar nossa ideia para ajudar.
What it does
Por meio da IA acompanhamos as famílias brasileiras realizando uma triagem de acordo com as métricas da OMS, esclarecemos fake news, diagnosticamos e direcionamos as medidas necessárias. Usamos o cep para construir o banco de dados e mapear picos de contaminação, número de pessoas no lar e grupos de risco. Insumo para futuros estudos.
How I built it
Só é possível através da tecnologia e inteligência artificial de hoje. Com IA, chatbot e whatsapp e acompanhamos individualmente as famílias.
Challenges I ran into
O tempo e a distância de trabalhar em equipe também tornou desafiador.
Accomplishments that I'm proud of
Identificar o meio de atingir os mais vulneráveis na pandemia e direcioná-los em um momento de incerteza, dúvidas e medos.
What I learned
O trajeto é tão bom quanto o final. As trocas de experiências e confiança no trabalho do time para no final unificar tudo e ter uma resultado incrível. Também entendemos como o vírus se comporta e o impacto que ele pode causar na população.
What's next for Dr. Li
Acreditamos que pode ser um meio de acompanhar as famílias que são mais carentes com maior frequência e baixo custo. Como próximos passos, pretendemos avançar com a nossa aplicação fazendo uma análise de predição para sabermos as próximas cidades, bairros que terão maiores picos da doença e estresse na saúde pública, e assim auxiliando o governo, para que possam tomar de decisões antes que a desordem ocorra. As próximas etapas também incluem um sistema integrado ao Chatbot para cadastrar psicólogos voluntários e conectá-los com as pessoas registradas pelo Dr. Li para uma terapia online e comunitária, e assim ajudando aqueles com problemas psicológicos causados durante a quarentena. Falando mais sobre as etapas do projeto, o Dr. Li será capaz de identificar e mapear famílias com dificuldades para receber o auxílio do governo, problemas socioeconômicos e muito mais.
Link para acessar apresentação completa com brand completo, investimentos e detalhes de funcionamento da ferramenta.:
https://drive.google.com/file/d/1X6Iypb70-X6YJq1n8FEL7ia7ERYi6X42/view?usp=sharing
Para visualizar um vídeo de um funcionamento do chatbot:
https://drive.google.com/file/d/1F2MgMw8ZRwtuWefFT06nuHzmOi7QZ3m0/view?usp=sharing
Para testar nossa aplicação, conversando com o Chatbot via WhatsApp, clique no link abaixo
https://api.whatsapp.com/send?phone=5511930200052&text=oi
Built With
ibm-watson
natural-language-processing
node.js
nosql
powerbi
Try it out
api.whatsapp.com | Dr. Li - Seu médico virtual | Usamos IA com o WhatsApp para interação com as famílias Brasileiras. Realizando a triagem, tirando dúvidas sobre o vírus, esclarecendo fake news, identificando sintomas e auxiliando as autoridades. | ['Joana Ritter', 'Clodoaldo Caldas', 'João Cardoso Oliveira Neto', 'Marta Caldas', 'Eduardo Moraes Ritter', 'Douglas Martins', 'Joel Pacheco Araujo - CHATBOT', 'Antonio Filipo de Mozer Namur'] | [] | ['ibm-watson', 'natural-language-processing', 'node.js', 'nosql', 'powerbi'] | 33 |
9,914 | https://devpost.com/software/verdadeiro-ou-fake | Logo
O usuário corretamente identifica uma notícia como verdadeira
O usuário pede pelo ranking do jogo
O usuário incorretamente identifica uma notícia como verdadeira, e recebe uma explicação provinda de agências verificadoras
O início do jogo
Inspiration
Conforme declarado pelo Organização Mundial da Saúde, a OMS, o surto de covid-19 está sendo acompanhado por outra epidemia: a infodemia. A infodemia nada mais é do que um excesso de informações - algumas precisas e outras não - que torna difícil encontrar fontes idôneas e informações confiáveis quando se precisa, levando à desinformação. No contexto de uma pandemia como a do novo coronavírus, a desinformação pode, inclusive, prejudicar a saúde da população e atrapalhar a implementação de políticas públicas necessárias.
Apesar de existirem diversas agências de verificação de fatos no país, muitas delas mantém esse conteúdo desenvolvido apenas em seus sites e redes sociais, dificultando a popularização do material produzido.
Por outro lado, é sabido que estabelecer uma conexão lúdica e emocional com o público é uma das melhores maneiras de conseguir fazer uma divulgação científica assertiva e que de fato mobilize.
Tendo tudo isso em vista, nos baseamos nos desafios D067, D110, D185 e D060, que estimulam tanto um produto voltado ao combate das fake news, quanto um jogo educativo relacionado ao novo coronavírus. Assim, desenvolvemos o “Verdadeiro ou Fake?”.
What it does
O “Verdadeiro ou Fake?" é um jogo educativo pensado para contribuir com a disseminação de informação precisa e acurada sobre o novo coronavírus. Esse novo jogo se passa inteiramente no aplicativo Telegram, a partir de uma conversa entre o usuário e um robô virtual. A medida que o jogo avança, o usuário vai recebendo uma série de notícias. Seu único trabalho é julgar se a notícia recebida é verdadeira ou falsa (fake). Todos os acertos são computados em uma pontuação pessoal, que é exibida ao longo do jogo. Além disso, o jogador também é capaz de acessar o ranking geral da pontuação do jogo e, assim, descobrir quem são os primeiros colocados da competição. Para programar o “Verdadeiro ou Fake?”, utilizamos tanto notícias falsas verificadas, quanto notícias verdadeiras veiculadas no site do Ministério da Saúde, em uma página especialmente dedicada às fake news.
How I built it
Buscamos por fontes confiáveis de verificação de notícias falsas, como por exemplo o Ministério da Saúde Brasileiro. Utilizando o API para construir bots do Telegram, e programando-o em Python. A base de dados contendo as notícias, seu valor de veracidade (verdadeiro ou fake) e a pontuação associada a cada notícia foi feita em SQL.
Challenges I ran into
Anteriormente ao projeto, nenhum de nós tinha experiência em programar bots de Telegram. Com isso, tivemos de rapidamente aprender como funciona o API, e como integrá-lo a um script em Python. Além disso, como todo programador lusófono já teve de fazer, problemas com compatibilidade de acentuação em Português tiveram de ser resolvidos em cada etapa do projeto.
Accomplishments that I'm proud of
Banco de dados composto por dois tipos de informações sobre o novo coronavírus: (1) informações falsas veiculadas pelo Whatsapp; (2) informações acuradas produzidas pelo Ministério da Saúde. (3) Um robô funcional que, de forma lúdica e facilmente escalável, treina usuários a distinguir notícias falsas de verdadeiras, assim promovendo um serviço à saúde pública.
What I learned
Aprendemos a utilizar o API do Telegram para programar bots, além de melhorar nossas habilidades organizacionais em um projeto de diferentes módulos. Aprendemos sobre melhores maneiras de comunicar ciência ao público e como fazer com que o aprendizado seja algo lúdico e leve.
What's next for Verdadeiro ou Fake
Qeueremos expandir o jogo para poder abarcar uma base de dados de fake news mais extensa, além de gerar estatísticas baseadas no resultado do jogo, uma vez que haja maior quantidade de jogadores. Tais estatísticas podem nos ajudar a entender quais são os tipos de notícia que mais enganam os usuários, assim fornecendo-nos uma importante ferramenta para combatê-las.
Built With
json
python
sql
telegram
Try it out
t.me | Verdadeiro ou Fake | E se pudéssemos combater as fake news do coronavírus brincando? Esse é o “Verdadeiro ou Fake?”, jogo educativo que ensina a população a diferenciar notícias verdadeiras de notícias falsas verificadas | ['Henrique Rocha', 'José Neto', 'Carolina Gigliotti', 'Clara Watanabe', 'carralas Carralas'] | [] | ['json', 'python', 'sql', 'telegram'] | 34 |
9,914 | https://devpost.com/software/biocheck-biossensor-para-diagnostico-da-covid-19 | Representação esquemática da leitura do resultado da medição do biossensor
Inspiration
Triagem de alto desempenho para COVID-19.
What it does
Biossensor com proteína S (específica para SARS-CoV-2) como biomolécula.
How I built it
Impregnação de biomoléculas em eletrodo impresso de carbono e construção de hardware acoplando sensor potenciométrico em Arduíno com conexão para aplicativo em celular.
Challenges I ran into
A equipe não conta com desenvolvedor para programação em Arduíno e desenvolvimento do aplicativo.
Accomplishments that I'm proud of
Estruturar uma proposta viável mesmo na ausência de desenvolvedor na equipe. Considerando que a solução, um vez bem estruturada, pode ser rapidamente executada a partir do momento que for incluído na equipe um desenvolvedor.
What I learned
Buscar fomas de viabilizar a transferência de conhecimento científico da academia para o mercado
What's next for BioCheck - Biossensor para diagnóstico da COVID-19
Desenvolver as etapas de programação, impregnar o suporte do biossensor com a biomolécula (proteína S, específica para SARS-CoV-2), calibrar o sistema e, no caso de querer os dados disponíveis em nuvem, conectar a um aplicativo.
Built With
arduino
potenciometro
sensor
Try it out
drive.google.com
drive.google.com
drive.google.com | BioCheck - Biossensor para diagnóstico da COVID-19 | Biossensor para diagnóstico da COVID-19 por detecção dos anticorpos IgM e IgG. Para triagem de alto desempenho e baixo custo é proposto o uso de Arduíno como potenciômetro. | ['Nathalia Teles Gomes Machado', 'Clarissa Moura', 'João Victor Nicolini'] | [] | ['arduino', 'potenciometro', 'sensor'] | 35 |
9,914 | https://devpost.com/software/ajudaaqui | Inspiration
Como se sabe a pandemia do coronavirus está afetando todo o mundo seja nas esferas econômicas ou de saúde tanto física quanto mental. Com essas consequências tão significativas a vontade de ajudar a população à enfrentar essa pandemia de alguma forma, nasceu.
What it does
Antes de pensarmos no que o aplicativo faz perguntas chaves foram pensadas, quais consequências estamos sofrendo ou iremos sofrer com essa pandemia? Perca de emprego, empresas fechando, pessoas precisando de ajuda, mais mulheres sofrendo violência doméstica e procurando quem pode ajudá-las, aumento de pessoas depressivas. São essas situações que queremos amenizar de alguma forma.
Sabemos a quantidade de informações dispersas que existem referentes a como ajudar, ser ajudado ou do que fazer nessa época de quarentena, essa situação é despendiosa quando se pensa em tempo e atrapalha muito no alcance e na ajuda mútua para a população e comunidade em geral.
A ideia é que o aplicativo seja um local central de postagens que acumula informações de outros sites separados em categorias de modo a diminuir o tempo na procura do que fazer, como ajudar outras pessoas nessa época de quarentena ou receber ajuda. As categorias são separadas em : "Doações", "Números de apoio", "Profissionalize-se", "DIY(faça você mesmo)", "Trate sua ansiedade", "Encontre uma ajuda psicólogica", "Ajude uma empresa local", "Ajude no combate ao coronavirus", "Aplicativos para atividades físicas", "Vagas", "Alimente sua mente"
Essas ajudas podem ser encontradas por links para vakinhas, links para sites de emprego ou cursos profissionalizantes, telefones de contato para psicólogos e de apoio (inclusive para mulheres que podem estar sofrendo com violência doméstica), além de encontrar atividades que auxiliam a diminuir o tédio ou a ansiedade das pessoas, ajudando-as portanto tanto economicamente quanto mentalmente. O site e o aplicativo mobile acumularia informações referentes a doações, cursos profissionalizantes, links para jogos, noticias e de modo que ajude as pessoas a encontrarem mais rápido modos a superar essa época. Algumas categorias podem ser filtradas pela região.
How I built it
Iremos ter as informações centradas em um site e um aplicativo mobile construídos em ionic tecnologia essa que facilita o desenvolvimento para web e mobile ao mesmo tempo (ios e android). Essa aplicação consumirá uma API em nodejs ou spring.
Challenges I ran into
Nosso desafio no momento centra-se em garantir recursos referentes a mantê-lo online, publicado nas plataformas web e mobile e manter também o servidor ativo e o seu desenvolvimento. Os desafios que foram adentrados nesse projeto envolve diversas áreas que foram afetadas pela pandemia, áreas econômicas e de saúde física e mental.
Accomplishments that I'm proud of
Nossos maiores feitos ainda serão realizados, mas nós orgulhamos de ser um time e de tentar ajudar de alguma forma a amenizar as consequências do covid.
What I learned
Aprendemos mais sobre os desafios que estão sendo enfrentados e vimos diversas formas que podemos ajudar nessa época ou posteriormente.
What's next for AjudaAqui
O próximo passo para a aplicação é finaliza-la e lançar nas plataformas disponíveis (play store e hospedar em um site) além de divulga-la para alcançar a população.
Built With
angular.js
ionic
java
node.js
spring
typescript
Try it out
github.com | AjudaAqui | Aplicativo voltado a ajuda na superação das consequências da pandemia Covid | ['Paulo Andrade', 'Kimbelly Ferraz', 'jadiel32', 'Edson Fagner da Silva Cristovam'] | [] | ['angular.js', 'ionic', 'java', 'node.js', 'spring', 'typescript'] | 36 |
9,914 | https://devpost.com/software/ephidia | Inspiração
Nos preocupávamos com o crescimento do número de casos de Covid-19 no Brasil, e em especial com a falta de informação dos cidadãos sobre número de contágios. Buscávamos uma maneira de dar uma visibilidade à ameaça, reforçando a necessidade de um isolamento consciente. No entanto, não sabíamos como propor uma solução que não envolvesse certa invasão de privacidade. Foi então que encontramos o artigo
“Decentralized Privacy-Preserving Proximity Tracing”
, divulgado pelo canal do YouTube “3blue1brown”, em conjunto com os desafios #D025 e #D149, que nos abriu os olhos para a possibilidade de garantir, ao mesmo tempo, informação e privacidade para os usuários.
O que faz o projeto
O aplicativo utiliza a tecnologia
Bluetooth Low Energy
(BLE), independente de acesso à geolocalização, para informar aos usuários o seu contato com infectados pelo coronavírus. O aplicativo promove uma emissão constante de códigos pseudo aleatórios. Com a proximidade de um outro celular, ocorre o registro e armazenamento dos códigos trocados no celular. No momento em que um dos usuários é diagnosticado com Covid-19, os códigos enviados pelo celular do infectado nos últimos 14 dias devem ser enviados a um banco de dados externo. Esse banco de dados, então, envia esses códigos via internet para todos os outros usuários, e cada aplicativo os compara com os códigos recebidos armazenados. Dessa maneira, os celulares que receberam os códigos do celular do infectado reconhecem esse contato e informam aos usuários a possibilidade de contágio para que se isolem. O aplicativo não só ajuda na adoção de medidas de isolamento mais eficazes, como também promove a saúde de seus usuários. Através do aplicativo, portanto, os usuários seriam informados sobre o contato com infectados pelo novo coronavírus de forma ágil e sigilosa, podendo se isolar e, assim, tomar as precauções necessárias para evitar o aumento na disseminação do vírus.
Como fizemos
Criamos um aplicativo em
React Native
, tendo como referência e como inspiração o projeto DP^3T (disponível em
https://github.com/DP-3T
). Para implementar a funcionalidade Bluetooth, utilizamos a biblioteca
React Native BLE Advertiser
(disponível em
https://github.com/vitorpamplona/react-native-ble-advertiser
).
Dificuldades que encontramos
Essa foi a primeira experiência do grupo com a criação de um aplicativo para celular. Tivemos ainda que aprender
React Native
. Achamos a configuração do ambiente de desenvolvimento e
build
para Android mal documentada na documentação do
React Native
, o que se apresentou como um complicador para o desenvolvimento do aplicativo. Além disso, não conseguimos fazer a comunicação entre o aplicativo e um servidor, mas acreditamos que com maior tempo e infraestrutura para o desenvolvimento da tecnologia isso seria possível.
Realizações das quais nos orgulhamos
Nos orgulhamos de termos construído uma demonstração do aplicativo com a funcionalidade Bluetooth implementada. Utilizamos uma biblioteca recentemente desenvolvida e implementamos essa nova tecnologia, buscando contribuir para a comunidade open source.
Também estamos satisfeitos com o nosso progresso como equipe: gerenciar um projeto com 11 pessoas foi um desafio concretizado com competência por meio do uso de diversas plataformas como Discord e Trello, e reuniões constantes para nos atualizarmos das atividades desempenhadas por cada um. A boa gestão da nossa equipe possibilitou que nossos integrantes trabalhassem com muito afinco e dedicação nas áreas que mais dominavam.
Além disso, nos sentimos realizados por dar visibilidade à ideia de um aplicativo que pode ajudar no enfrentamento da pandemia sem abrir mão da privacidade dos usuários. O Hackathon nos deu a oportunidade de contribuirmos para a luta contra o novo coronavírus, e acreditamos que a solução que propusemos pode vir a ter um papel relevante para a comunidade.
O que aprendemos
Ao ler os desafios e refletir sobre possíveis soluções, descobrimos diversas iniciativas já existentes para a melhoria do Sistema de Único de Saúde e para o combate ao novo coronavírus.
Aprendemos a desenvolver um aplicativo para android e a implementar
Bluetooth Low Energy
(BLE) com
React Native
.
Passamos a olhar com maior atenção para a questão da privacidade e constantemente nos deparamos com encruzilhadas nas nossas próprias ideias. Assim, durante o desenvolvimento do aplicativo, tivemos que ficar alertas para contornarmos possíveis contradições na nossa proposta.
Próximos passos
A partir do momento que um usuário é diagnosticado com Covid-19, é necessário que o seu médico envie os códigos emitidos pelo seu celular nos últimos 14 dias para o banco de dados externo. Isso poderia ser feito por uma versão para médicos do aplicativo que solicitaria acesso aos dados do celular do paciente e enviaria para o banco de dados, sem que houvesse identificação do usuário infectado e que fosse de fácil manuseio para os profissionais da saúde. Essa versão para médicos poderia exigir o CRM e a assinatura eletrônica do médico, e deveria ser suficientemente segura para que somente esses profissionais tivessem acesso.
Pensamos que a verificação dos códigos do banco de dados pelo aplicativo pode ser feita enquanto houver internet, mas que a notificação do contato com algum infectado pelo coronavírus só ocorresse duas vezes por dia. Essa estratégia reforça o conteúdo anônimo do aplicativo, já que o reconhecimento do contato não é feito imediatamente, além de não gerar um medo constante do contágio. Ao mesmo tempo garante uma frequência alta de checagem.
Como o objetivo desse aplicativo é que seja utilizado em larga escala (em grandes cidades, em estados ou até mesmo no país inteiro), a versão apresentada ao público deve ser validada em um projeto piloto. É interessante, portanto, que esse aplicativo seja testado inicialmente em alguma cidade pequena, para que se possa ter uma melhor compreensão do seu alcance e utilização. Dessa maneira, poderiam ser identificados pontos de melhoria e poderiam ser adicionadas novas funções a ele.
Para que o aplicativo seja eficaz, é necessário que uma porcentagem considerável da população o utilize. Para estimular o público a baixá-lo, pensamos na realização de parcerias com empresas que prosperam no contexto da quarentena. Serviços de entrega domiciliar poderiam dar descontos àqueles que baixarem ou que tiverem o aplicativo em seus celulares como forma de propaganda e incentivo. Serviços de
streaming
e jogos eletrônicos poderiam divulgar e oferecer vantagens àqueles que tiverem o aplicativo. Além disso, poderíamos contatar hospitais, clínicas e laboratórios de exames para que divulgassem o aplicativo ao público geral.
Seria interessante que o aplicativo tenha um
risk score
dinâmico que seria baseado no número de códigos recebidos provenientes de pessoas infectadas e que refletiria o tempo de contato com infectados. Poucos códigos recebidos de infectados significaria um contato muito curto, com pouco risco de contágio, enquanto muitos códigos recebidos de infectados significaria um contato mais prolongado e, por isso, um maior risco de contágio. Assim, só haveria necessidade de notificação nos casos em que o usuário recebeu um número de códigos de infectados acima de um número pré-estabelecido. Esse número poderia ser estabelecido por autoridades de saúde com base em estudos a respeito do tempo de contato necessário para a transmissão do vírus.
Built With
android-studio
flask
javascript
marshmallow
python
react-native
react-native-ble-advertiser
sqlalchemy
Try it out
github.com
drive.google.com | Ephidia | Por meio do envio de códigos a aparelhos próximos, o aplicativo utiliza tecnologia Bluetooth para informar aos usuários, de forma sigilosa, a possibilidade de terem sido infectados pelo coronavírus. | ['Isabela Paro', 'Filipe Nobre', 'Miguel Araujo e Silva', 'Carolina Fraga', 'Luiz Palhano', 'Aline Fragas', 'Daniel Coelho', 'Bento Maranhão', 'Carolina Paro', 'Clara Tavares', 'Felipe Faria'] | [] | ['android-studio', 'flask', 'javascript', 'marshmallow', 'python', 'react-native', 'react-native-ble-advertiser', 'sqlalchemy'] | 37 |
9,914 | https://devpost.com/software/frontcovid-19 | FrontCOVID-19 - Profissionais na linha de frente, nossa preocupação é a sua saúde.
Descrição resumida do projeto
Em virtude da exposição no ambiente de trabalho, elevados índices acometimento pelo novo coronavírus têm sido observados em profissionais atuando no setor saúde nas redes pública e privada no contexto da pandemia da COVID-19. Nossa iniciativa visa dar a oportunidade a estes profissionais de relatarem situações de risco no ambiente de trabalho e ainda da população geral relatar por empatia se testemunhou alguma situação de vulnerabilidade. Identificado o problema, o responsável/gestor terá o direito de resposta assegurado sobre a situação relatada e poderá declarar eventuais medidas tomadas garantindo sua resolutividade. Tal visibilidade e mapeamento de riscos e vulnerabilidades, tem o intuito de favorecer a redução desses indicadores, além de dar maior segurança no ambiente ocupacional, acolhimento e possibilidades de apoio psicológico e informar sobre aspectos jurídicos aos profissionais
Inspiração
Temos acompanhado com angústia o acometimendo crescente de profissionais atuando no setor saúde na linha de frente na resposta à epidemia da COVID-19 no Brasil. Estes profissionais devem se sentir seguros no ambiente de trabalho, portanto estes locais precisam adotar medidas que garantam a saúde dos trabalhadores e oferecer condições para a não sobrecarga de trabalho. Além disso, percebe-se a necessidade de apoio psicológico dada a exposição a situações de vulnerabilidade emocional e estresse ocupacional.
O que faz o projeto?
Nossa plataforma possibilita a identificação e mapeamento de riscos e vulnerabilidades com a finalidade de reduzir exposição à infecção, adoecimento e óbitos, além de buscar proporcionar maior segurança no ambiente ocupacional, possibilidades de apoio psicológico, orientações para melhor preparo e informar sobre aspectos jurídicos aos profissionais do setor saúde atuando na linha de frente no enfrentamento da epidemia de COVID-19 nas redes pública e privada no Brasil
Como fizemos?
Busca de referências para caracterização do problema e levantamento dos principais fatores associados com o problema. Para viabilizar a plataforma, dividimos o trabalho na organização dos formulários com as informações importantes a serem levantadas, criação do banco de dados, integração com google maps (em andamento), design da logo e telas do projeto e integração das diferentes atividades conjuntas na plataforma. Além disso, houve colaboração externa na validação do questionário com o publico alvo e assesoria jurídica.
Dificuldades encontradas
Tempo disponível para construir a ferramenta
Hackers e mentoria dialogando em diferentes locais no mundo com diferenças de horário (Brasil, Nova zelândia e Inglaterra)
Realizações das quais nos orgulhamos?
Construção colaborativa da ferramenta
Redes de contatos, parcerias e amizades construídas no processo
O que aprendemos?
Necessidade de dar visibilidade por empatia a um grupo de profissionais que têm se exposto a riscos maiores em prol do coletivo
Importância do acolhimento, resolutividade e valorização do SUS
Ciência e tecnologia na redução de vulnerabilidades preservando a saúde do trabalhador
Diálogos com o público alvo
Criatividade e construção coletiva
Pensar a saúde de quem cuida é pensar a saúde coletiva
Próximos passos?
Desenvolvimento de aplicativos para dispositivos móveis (app mobile)
Link para os participantes experimentarem o que foi desenvolvido
link
Equipe e colaboradores do projeto
Hackers: Desenvolvimento (Vitor Diniz, Paola Sanchez, Luziana Assunção) e Design (Silvia Batalha)
Mentoria: Dr. David Soeiro Barbosa
Colaboradores externos
Revisão e validação: Dr. Carlos Leonardo Figueiredo Cunha
Assessoria Jurídica: Samuel Duarte (Bacharel em Direito)
Validação: Felipe Ridolfi (Médico infectologista) e Raquel Soeiro (Enfermeira)
Built With
adobe-illustrator
css
html5
javascript
node.js
photoshop
react
react-native
sqlite
Try it out
frontcovid19.netlify.app | FrontCOVID-19 | Nossa iniciativa possibilita a identificação e mapeamento de riscos e vulnerabilidades de profissionais do setor saúde na linha de frente visando reduzir o acometimento destes pelo novo coronavírus | ['Paola Palencia', 'Luziana Assunção', 'Silvia Batalha', 'Vitor Diniz'] | [] | ['adobe-illustrator', 'css', 'html5', 'javascript', 'node.js', 'photoshop', 'react', 'react-native', 'sqlite'] | 38 |
9,914 | https://devpost.com/software/9mesesdepois | App De Olho na Gestação: Cuidando de quem cuida
Inspiração
Diante do atual momento de isolamento social que o novo coronavírus impõe, as pessoas se tornam mais suscetíveis a abalos emocionais e psicológicos, além de preocupações financeiras que se colocam frente a insegurança laboral. Tendo em vista que o momento da gestação em um contexto normal já pode gerar insegurança a gestantes e seus familiares, no momento de pandemia essas pessoas encontram pouco apoio e acolhimento no sistema de saúde, que se encontra colapsado com os casos mais graves da doença, bem como o isolamento impossibilita o contato com entes queridos. Assim, nossa inspiração é ajudar gestantes e seus familiares a atravessarem esse momento, oferecendo um espaço de trocas e acolhimento, possibilidades de apoio, informações jurídicas a respeito de leis para gestantes, bem como solucionando dúvidas a respeito de exames e consultas.
O que faz a solução?
O aplicativo móvel possibilita a troca de experiências entre gestantes através dos fóruns de discussão, que conta também com a participação de profissionais de saúde e acadêmicos, tornando-se uma alternativa para suprir os encontros de gestantes suspensos, que eram oferecidos pelas Unidades Básicas de Saúde. Além disso, o App traz informações úteis de como proceder em cada etapa da gestão, tendo em vista o cenário de isolamento social e risco de contágio, com dicas de exercícios e alimentação, como se prevenir do novo coronavírus e informações jurídicas.
Como foi construído?
A solução foi construída através do ambiente de desenvolvimento Android Studio, focada no desenvolvimento de aplicativos para dispositivos móveis.
Desafios encontrados
O tempo foi nosso maior desafio, pois a implementação de determinadas soluções demanda tempo de estudo e entendimento da problemática, bem como compreensão da melhor ferramenta e como implementá-la, além é claro de tempo para a construção da solução.
Realizações
Construção de redes de apoio e colaborativas.
Aprendizado
Empatia pela maternidade e seus contextos, dando importância ao acolhimento de gestantes e familiares a espera de uma nova vida, de uma criança, que não deixa de ser símbolo de esperança no futuro.
Próximos passos do App De Olho na Gestação
Posteriormente iremos implementar todas as ferramentas para o bom fucionamento do App, buscaremos contactar órgãos responsáveis para a implementação de projeto piloto em Unidades Básicas de Saúde.
Built With
android-studio
Try it out
github.com | De Olho na Gestação | Em virtude do novo coronavírus o período de gravidez está marcado por muitas inseguranças. Nesse contexto, pensou-se uma solução que possa conectar gestantes em prol de ampliar acolhimento e apoio. | ['Emilly Marques', 'Tainá Oliveira', 'Luiz Lopes'] | [] | ['android-studio'] | 39 |
9,914 | https://devpost.com/software/duca | Inspiration
A inspiração do projeto vem da teoria Piagetiana que diz que, no período pré-operatório (2 a 8 anos), as crianças adquirem a função da linguagem, que edifica as relações pessoais e o simbolismo. Dessa forma, necessitam de jogos lúdicos e da exploração do conteúdo por si mesmas para que haja um aprendizado saudável, baseado nisso, criamos uma plataforma que permitisse o aprendizado escolar ministrado por um professor com a junção de tarefas criativas e que permitam que a criança explore por si só o conteúdo, como os desafios semanais. Além de promover um Diário da quarentena sendo preenchido por elas,da maneira que decidirem (texto ou figuras), que permite não só que se aflore a criatividade, mas também reforça a empatia e as relações pessoais entre discentes e entre docente e discentes nesse momento de distanciamento social.
What it does
O projeto permite uma nova forma de educação em tempos de EAD. Sabemos que a educação não se resume apenas à racionalização das disciplinas incluídas no currículo escolar, mas as experiências desenvolvidas do contato humano e da rotina estabelecida. Assim, nosso projeto visa atenuar as consequências do distanciamento social na educação através de ferramentas que proporcionam um ambiente lúdico e o contato com os valores mais essenciais em tempos de pandemia, como a empatia, a solidariedade, a inclusão e a criatividade.
How I built it
Após pesquisas sobre o cenário da educação brasileira após o início da pandemia, foram reunidos informações relevantes em relação às adversidades enfrentadas pelos professores, pelos alunos e pelos pais diante da educação não presencial. Além disso, foi identificado uma certa desorganização e desorientação para as atitudes que as escolas deveriam tomar.
Levando em consideração toda a pesquisa, decidimos qual tipo de plataforma traria a melhor experiência para a maioria dos usuários e qual seria o melhor estilo de design a ser aplicado. Dessa forma, foi planejado os layouts e recursos principais e foi criado um protótipo de um aplicativo por intermédio do AdobeXD, levando em consideração a imagem lúdica e acessível do app.
Nossa expectativa é continuar com essa ideia, e desenvolver o projeto por completo.
Challenges I ran into
Durante a idealização, tivemos que aprender mais sobre acessibilidade digital e como tornar o processo de aprendizagem mais lúdico e interessante para crianças. Além disso, tivemos que decidir qual plataforma seria utilizada e como seria disponibilizado manual de uso para pais e professores.
Accomplishments that I'm proud of
Durante o processo de desenvolvimento da ideia do projeto, estivemos pensando sempre em três frentes: o aluno, o professor e os pais. A fim de alcançar o máximo de pessoas possível, procuramos desenvolver uma plataforma que cumprisse as recomendações do Modelo de Acessibilidade em Governo Eletrônico. Além disso, pensamos em atividades que aproximam os pais na educação de seus filhos e aprendemos a mexer no Adobe XD. Mas, a realização de que mais nos orgulhamos, é idealizar uma plataforma com um ambiente que incentive a criatividade, o desenvolvimento emocional e a empatia mesmo em tempos de distanciamento social.
What I learned
Aprendemos que a internet possui os recursos necessários para a criação de ambientes de aprendizagem colaborativa, onde alunos e professores participam ativamente na construção do conhecimento. Dessa forma, o aluno também desenvolve competências como o senso crítico, a imaginação e a ajuda ao próximo.
Além disso, a atualidade e a super utilização de meios eletrônicos constroem um mundo hiper racionalizado, que vai de encontro a teorias fundamentais do conhecimento. Aprendemos que o reconhecimento dessa falha e da necessidade de se valorizar aspectos subjetivos como a conversa impessoal, a brincadeira e a imaginação são ferramentas ímpares no enfrentamento de um período de distanciamento, especialmente na formação de crianças.
What's next for Duca
A criação de avatar para os alunos, para que esses possam interagir ainda mais com a plataforma e mudar seu avatar conforme cumprem com os desafios avaliativos propostos pelos professores. Além de criar um manual do método proposto aos professores e desenvolver completamente o aplicativo.
Built With
adobe-illustrator
adobexd
premiere
Try it out
xd.adobe.com | Duca: Educação digital para crescer e aprender | A fim de melhorar a experiência dos envolvidos no processo de ensino em situações inesperadas, que resultam no apelo digital, foi criado o "Duca", visando sempre fortalecer a relevância da educação. | ['Samanta Silva', 'Amanda Ribeiro', 'Mariana Penteado Sacchi', 'Kaori Yamashita', 'Renan Ornaghi', 'Isadora da Costa Barro Novo'] | [] | ['adobe-illustrator', 'adobexd', 'premiere'] | 40 |
9,914 | https://devpost.com/software/d150-saude-sistema-l-bgenetica | Logo
Inspiration
Brasil está enfrentando um colapso financeiro e econômico, e decidimos ajudar criando uma tecnologia para combater o vírus.
What it does
Sistema revolucionário de inteligência artificial para o Brasil e para o mundo, que auxiliará na tomada de decisões em tempo real, para prevenção e combate a pandemias.
O sistema Análise Genética, será uma ferramenta eficaz para tomada de decisão mais rápida. A mutação do vírus será detectada em tempo real. Atualmente já existem máquinas que fazem o sequenciamento do dna e rna em minutos, todavia, o sistema Análise Genética tem uma complexidade no grau de dados, capaz de identificar e mensurar a mutação e evolução do vírus, facilitando o trabalho dos Virologistas, através de indicadores para a elaboração da vacina.
O sistema de inteligência artificial, tipifica todas as bases encontradas no DNA e RNA (genoma do vírus).
Dentro deste contexto, o objetivo geral desta proposta é estabelecer uma proteção ao Brasil contra pandemias, no qual a ferramenta possa ser empregada para análises acerca de diversas pandemias causadas por agentes transmissores sazonais, que dependam de condições climáticas; localização geográfica e genética da população, como é o caso não só do Coronavírus, como também, a dengue que é provocada pelo mosquito Aedes Aegypts; a H1N1, entre outras pandemias.
Reitero que o projeto é a nível de conhecimento genético e sempre que o Brasil necessitar combater pandemias, estaremos à disposição.
How I built it
Construímos criando um protótipo de alta fidelidade em tecnologia web; ferramentas de edição de vídeo para criação da apresentação e estudos arduos na área de virologia.
Challenges I ran into
Dificuldades em conseguir dados genéticos.
Accomplishments that I'm proud of
Adquirimos bastante conhecimento no âmbito de virologia.
What I learned
Várias etapas cruciais para idealizar este projeto focado em mutações de vírus.
What's next for D150- Saúde- Sistema L&BGenética
Etapas posteriores do projeto:
Iremos expandir a plataforma na criação de detectar a mutação do vírus por Região geografica, tipos de proteinas e aminoácidos. será possivel analisar o gráfico por região geográfica; investigar os detalhes que representam as proteínas que cada vírus é composto, permitindo observar a evolução de cada proteína em indicadores de desempenho, facilitando na tomada de decisões para a criação da vacina de maneira mais assertiva.
Built With
analytic
data
ia
machine-learning
web
Try it out
lbgenetica.solucoeslb.com.br | D150- Saúde- Sistema L&BGenética | Sistema que permite realizar previsões na mutação de vírus, contribuindo para a elaboração de vacinas e medicamentos. | ['Laís Silva'] | [] | ['analytic', 'data', 'ia', 'machine-learning', 'web'] | 41 |
9,914 | https://devpost.com/software/d088-trazer-monitoramento-de-contatos-entre-as-pessoas | Tela principal
Rastro de movimentação de pessoas
Declaração de sintomas e resultados de exames
O que motivou a minha idéia?
A transmissão do vírus, especialmente nos casos de pessoas assintomáticas, é um problema complicado de se revolver. O que leva a uma solução de rigoroso distanciamento social.
Também é sabido que a oferta de testes para a Covid-19 é um recurso limitado.
Como poderíamos utilizar a tecnologia para estimar o risco de contágio e desta forma poder aplicar melhor os recursos e as regras de distanciamento social?
Minha proposta
Desenvolver um aplicativo que estime o risco de contágio, considerando as seguintes informações:
1 - Monitoramento de contato com outros usuários do aplicativo através do uso capacidade de geolocalização presente nos smartphones.
2 - Autodeclaração de sintomas e resultados de exames
Mais detalhes no documento anexo
Built With
.net
android-studio
azure
c#
kotlin
sql
Try it out
drive.google.com
docs.google.com | D088 - TRAZE - MONITORAMENTO DE CONTATOS ENTRE AS PESSOAS | Aplicativo para smartphone que tem o objetivo de ajudar a estimar o risco de contágio do Covid-19 com base no monitoramento dos contatos entre as pessoas e dos sintomas autodeclarados | ['davi martins'] | [] | ['.net', 'android-studio', 'azure', 'c#', 'kotlin', 'sql'] | 42 |
9,914 | https://devpost.com/software/esteja | Logo
(Este)r Sabino: uma das responsáveis por sequenciar o genoma do coronavírus em apenas 48 horas
(Ja)queline Goes (ao centro): uma das responsáveis por sequenciar o genoma do coronavírus em apenas 48 horas
Página inicial da plataforma
Página de auxílio ao diagnóstico
Inspiração:
Segundo dados do
Painel Coronavírus
, plataforma atualizada diariamente pelo Ministério da Saúde com o objetivo de ser o veículo oficial de comunicação sobre a situação epidemiológica do coronavírus no Brasil, hoje, 17/05/2020, contamos com cerca de 233.142 casos confirmados, sendo 15.633 o número de óbitos até o dado momento. Tragicamente, tais números nos colocam à frente de países como a Itália e a Espanha no que tange ao número total de casos causados pelo vírus.
Motivados por esta problemática, inspirados pela vontade de auxiliar a sociedade como um todo e baseados no desafio D-051, do Hackcovid-19, que sugestiona a Ciência de Dados como potencial ferramenta de embate à pandemia, nosso time tirou ideias do papel e trouxe à tona uma solução:
EsteJa, a plataforma de auxílio ao diagnóstico de COVID-19
. Seu nome é uma homenagem às pesquisadoras brasileiras
(Este)
r Sabino e
(Ja)
queline Goes, que sequenciaram o genoma do coronavírus em apenas 48 horas.
O que faz?
A EsteJa utiliza aprendizado de máquina para inferir se o paciente precisa ou não de atendimento especializado a partir de dados dos seus exames. Ao inserir estes dados, a ferramenta indica ao médico se o paciente analisado possui perfil comum aos demais infectados pelo COVID-19. A partir dessa análise, o médico possui subsídio estatístico para que as suas decisões sejam melhor tomadas em relação ao encaminhamento do paciente.
Como construímos?
A plataforma EsteJa é disponibilizada em uma aplicação web desenvolvida com Django, Javascript e Python e utiliza o modelo Decision Tree J48, treinado com o auxílio do software Weka na
base disponibilizada pelo Hospital Israelita Albert Einstein
. Os dados utilizados foram pré-processados e estudados de forma a possibilitar o alcance de resultados satisfatórios em detrimento da pouca quantidade de dados e do pouco tempo disponível para o desenvolvimento.
Desafios:
O maior desafio enfrentado pelo grupo foi o esparsamento dos dados relacionado ao vírus no Brasil. A base utilizada (a melhor encontrada nas pesquisas realizadas pelo time) possuía, inicialmente, 5644 observações de 111 variáveis; depois de realizado o pré-processamento - que primou em manter a maior proporção de registros x variáveis possível (uma vez que não adotamos registros com quaisquer campos nulos) - restaram apenas 598 observações de 16 variáveis. Além disso, outro grande desafio foi o pouco tempo disponível para integrar uma equipe com skills distintas, idealizar a ferramenta e, o mais importante: tirá-la do papel.
Feitos dos quais nos orgulhamos!
Nos orgulhamos de, apesar das numerosas limitações, termos alcançado a marca de 84,28% de classes corretamente classificadas. Das 598 observações, 478 foram classificadas como negativo para COVID-19 sendo realmente casos negativos; 26 foram classificadas como positivo sendo verdadeiramente positivos; 39 foram classificadas como positivo sendo, na verdade, negativos; e 55 foram classificadas como negativo sendo, na verdade, positivos.
Certamente, com maior tempo para desenvolvimento/análise estatística e uma base menos esparsa em mãos, os resultados tornar-se-iam ainda mais expressivos.
O que aprendemos:
Além de aprendermos aspectos relacionados ao COVID-19 - que nunca antes havíamos parado para refletir - e de nos atentarmos mais a questões como a subnotificação de casos no Brasil e no mundo, este hackathon foi uma oportunidade para saírmos de nossa zona de conforto (já que a equipe é formada por pessoas de diferentes universidades, de diferentes cursos e com diferentes habilidades), trabalharmos em conjunto e desenvolvermos uma ferramenta com potencial para ajudar milhares de pessoas. De certa forma, também aprendemos a superar as limitações existentes, uma vez que os dados utilizados, referentes ao coronavírus no Brasil, enfrentam grande esparsamento.
É importante citar que o esparsamento de dados merece destaque e necessita de auxílio/esforço tanto de entidades governamentais como de entidades não-governamentais. Ao tornar mais e mais dados públicos e acessíveis, possibilita-se o surgimento e o aprimoramento de outras ferramentas como a EsteJa, que tem por objetivo zelar pelo bem-estar e saúde da população.
Próximos passos para a EsteJa:
Mais dados para melhorar as inferências
Testar outros modelos para comparar as performances
Feature Engineering para correlacionar dados e encontrar conexões importantes que melhorem a qualidade do modelo.
Login e senha para acessar a aplicação
usuário de teste: teste e senha: teste@esteja
Built With
bootstrap
css3
django
html5
javascript
python
Try it out
esteja2020.pythonanywhere.com | EsteJa | Plataforma de auxílio ao diagnóstico de COVID-19. | ['Renan de Oliveira da Cruz', 'Joao Pedro Almeida Santos Secundino', 'Ana Paula Mendes'] | [] | ['bootstrap', 'css3', 'django', 'html5', 'javascript', 'python'] | 43 |
9,914 | https://devpost.com/software/covidtrack-rjkati | Inspiration
Decidi escolher essa ideia por ser bastante simples e barata de implementar, já que não será necessário nenhum hardware adicional (somente um smartphone). Poderá ajudar muito as autoridades sanitárias a rastrear pessoas possivelmente infectadas.
What it does
Quando o usuário executa o aplicativo, este inicia a captura dos endereços MAC de todos os dispositivos bluetooth que estiverem no alcance e os envia para um servidor, onde uma API está sendo executada. A API armazena em um banco de dados esta lista de aparelhos relacionada à este usuário específico.
Assim que o usuário recebe a confirmação de que está com a doença, ela reportará ao sistema (ainda não implementado). Assim, pode-se obter a lista de todos os dispositivos bluetooth com os quais a pessoa teve contato no momento que estava infectado. Tendo em vista que a tecnologia bluetooth tem curto alcançe, é provável que as pessoas portando os aparelhos que estão na lista também tenham sido expostas ao vírus.
Munidas desses dados, autoridades sanitárias poderiam andar em locais públicos com sensores bluetooth para detectar se uma pessoa potencialmente infectada está por perto.
Outra possível funcionalidade é enviar um alerta a um usuário assim que este entrar em contato próximo com outro usuário cadastrado no sistema que esteja infectado (ainda não implementado)
Este primeiro protótipo que será apresentado ao Hackathon contém apenas a API, migrações para o banco de dados e o aplicativo para android com a funcionalidade principal implementada (captura e envio dos endereços MAC).
Tanto a API como o aplicativo foram testados e estão funcionando conforme o esperado. A lista de endereços MAC é gerada no banco normalmente.
How I built it
A API foi construída a partir do framework php Laravel. Deve-se gerar o banco de dados através da migrations e seeds do framework.
O aplicativo Android foi programado em linguagem Kotlin, utilizando a ferramenta Android Studio. As requisições para a API são envidas utilizando a biblioteca Volley, do Android.
Não foi utilizado georeferenciamento, em respeito à privacidade dos usuários.
What I learned
Aprendi muito sobre o desenvolvimento de aplicativos REST mobile e suas respectivas APIs, experiência que certamente será útil no mercado de trabalho.
What's next for Covidtrack
Se os realizadores do Hackathon decidirem por dar continuidade a este projeto, irei procurar desenvolvedores parceiros para implementar as funcionalidades que faltam, transformando o protótipo em produto final. Também conheço designers que podem contribuir com o layout final, publicidade e interface de usuario do aplciativo.
Agradeço à Fiocruz, ao CBPF e demais relizadores do evento por esta oportunidade.
Built With
android
kotlin
laravel
php
volley
Try it out
github.com
github.com | Covidtrack | Uma ideia simples e barata para encontrar pessoas infectadas, usando a tenologia bluetooth dos smarthphones. | [] | [] | ['android', 'kotlin', 'laravel', 'php', 'volley'] | 44 |
9,914 | https://devpost.com/software/unified-system-for-artificial-ventilation-equipment-u-save | U-SAVE
Aquisição dos dados!
Um dos setup experimentais.
Nosso Arduino em ação!
Webcam no local onde acontece os experimentos para ajudar na configuração remota.
Nosso sensor
O protótipo!
O protótipo funcionando!
E assim fazemos o trabalho de forma remota
Esquematico do Projeto
Nossa equipe trabalhando juntos.... remotamente....
Inspiration
O Brasil iniciou maio com um total de 91.589 confirmados casos de COVID-19. Até o dia 15 de maio, havia 218.223 casos totais, um aumento de 2,4 vezes em apenas duas semanas.
Destes, 19.987 casos estão no Rio de Janeiro, o quarto estado com o maior número de mortes por milhão de habitantes. Só no estado do Rio de Janeiro foram mais de 2.400 mortes pela doença até 15 de maio.
Esses números de mortes se devem muito à falta de leitos com ventiladores pulmonares.
Os valores de ventiladores pulmonares comerciais estão na faixa de R$ 25.000,00 a R$ 50.000,00, representando um elevado custo aos cofres públicos e privados, impedindo a destinação de recursos a outros produtos que porventura sejam necessários.
Neste contexto de pandemia de COVID-19, diversas soluções de ventiladores pulmonares foram propostas. Todas essas soluções são bem vindas, mas oferecem um elevado risco à integridade física do paciente, com possível comprometimento do tecido pulmonar e vias aéreas (podendo causar danos permanentes, se não fatais) se não garantirem a segurança respiratória do paciente.
Assim, para permitir segurança e acessibilidade na assistência ventilatória dos pacientes acometidos por COVID-19 é necessário um
sistema capaz de avaliar a estabilidade e segurança imediata e especialmente continua da assistência ventilatória destes pacientes.
Tal projeto deve ser aplicável a qualquer equipamento já construído ou que venha a ser proposto. Garantindo uma uniformidade nos padrões de segurança nessa situação de emergência. Permitindo a viabilidade de projetos mais simples em locais de menos recursos. E disponibilizando um dispositivo de segurança extra.
Our Goal
O projeto deste sistema de monitorização de respiração forçada em ventiladores/respiradores de emergência foi proposto por Luis Miguel Domingues Mendes. Essa demanda inspirou o insight valioso para este momento que vivemos, dando origem ao U-SAVE (Unified System for Artificial Ventilation Equipment).
Nosso objetivo é garantir a segurança dos pacientes a partir da implementação de um sistema de alarme e monitoramento em tempo real de uso comum a diversos ventiladores mecânicos. Para além da segurança do paciente, um sistema de monitoramento comum poderá facilitar a operação dos profissionais de saúde, na verificação das parametrizações de operação de ventiladores para segurança respiratória cada paciente.
As seguintes metas nos guiaram na busca de uma solução para este desafio:
Exibir o protótipo do U-SAVE (Unified System for Artificial Ventilation Equipment) exibido no Hackcovid19;
Obter a aprovação e validação do projeto junto ao corpo de jurados do Hackcovid19;
Buscar financiamento para a primeira colocação do sistema no mercado.
Product Market-fit ;
Transformar o protótipo em um MVP até o fim de maio;
Estar com o produto em funcionamento e viabilizando os projetos de ventiladores pulmonares ainda no início de junho.
What it does
O U-SAVE (Unified System for Artificial Ventilation Equipment) é um sistema de monitoramento não específico para equipamentos de ventilação pulmonar, que visa garantir a segurança dos pacientes. Tal projeto pode contribuir para o suporte seguro a pacientes acometidos pela COVID-19 em adição aos inúmeros projetos de ventiladores que estão sendo disponibilizados e reproduzidos a baixo custo, para atender ao cenário de pandemia.
Assim, o sistema foi desenvolvido para garantir a segurança aos pacientes hospitalizados que necessitem do uso de qualquer equipamento de ventilação pulmonar produzido neste momento de pandemia.
Para isso, o sistema monitora e apresenta em uma tela de LCD a curva de respiração. Utilizando um sensor de pressão, o sistema monitora de forma contínua se os seguintes parâmetros estão dentro dos níveis de segurança:
Pressão Inspiratória Positiva (PIP);
Pressão Expiratória Final Positiva (PEEP);
Taxa de respiração;
Relação inspiração/tempo de expiração (I/E).
Qualquer parâmetro fora dos níveis de segurança aciona um alarme sonoro e um luminoso para avisar o profissional de saúde. O sistema também apresenta a curva de respiração em uma tela LCD.
How We built it
O desenvolvimento deste sistema, foi realizado remotamente com um arranjo experimental instalado no Centro Brasileiro de Pesquisas Físicas (CBPF). Para avaliação do sistema de monitoramento, foi utilizado o ventilador de emergência OpenAir.
O projeto é composto por uma plataforma de prototipagem Arduino Mega 2560 conectado a uma tela LCD, LEDs, Buzzer Piezoelétrico e sensor digital de baixas pressões.
O Arduino foi configurado para fazer a aquisição digital do sensor de baixa pressão e apresentar a curva de pressão na tela LCD. Para confirmar os valores medidos de pressão e verificar oscilações, foram realizados diversos testes com auxílio de uma coluna de água.
Testes foram feitos em um ventilador de emergência (OpenAir) para verificar se todos os parâmetros estão sendo adquiridos de forma correta. Também foram testadas várias situações de operação.
O sistema de monitoramento do U-SAVE verifica o atendimento dos níveis de segurança respiratória do paciente conectado à ventilação mecânica. Ao detectar situações de risco, o sistema aciona um aviso sonoro (buzzer piezoelétrico) e um aviso luminoso (LEDs).
Para tanto, os componentes empregados neste projeto foram:
Arduino MEGA 2560;
LCD TFT screen 2.8″ ILI9341;
Sensor de baixa pressão (HSCMAND160MD2A5).
Adicionalmente, foi utilizada uma webcam para suporte ao desenvolvimento remoto do projeto.
Challenges We ran into
Um dos maiores desafios encontrados nesse momento foi tentar trabalhar à distância, não apenas dos outros integrantes, mas do próprio equipamento.
O gerenciamento do time e dos prazos foi um desafio adicional, com a comunicação limitada devido ao distanciamento. Saímos do nosso ambiente de trabalho ao qual estávamos acostumados.
O distanciamento do equipamento, a dependência de uma pessoa física no local que pudesse realizar o experimento, e a limitação do tempo, limitaram os testes realizados. Foi necessária também a utilização de webcam para acompanhar os experimentos com o hardware.
Outro desafio foi acessar remotamente ao ambiente de desenvolvimento, garantindo a segurança cibernética durante a comunicação e velocidade de desenvolvimento do projeto,
Mais um dos desafios encontrados foi desenvolver todo projeto com componentes de fácil acesso e baixo custo. Um exemplo deste desafio, foi em como programar a visualização dos parâmetros e da curva de respiração na tela de LCD, de maneira a facilitar a vida dos profissionais de saúde.
Accomplishments that we are proud of
Apesar dos desafios relacionados à distância e instrumentação, implementamos o protótipo de um sistema de alarme e monitoramento em tempo real para ventiladores mecânicos de baixo custo que possa ser usado para alertar profissionais de saúde caso algum parâmetro fique fora dos padrões de segurança.
Assim, participamos de um projeto de um sistema que para além da segurança do paciente, um sistema de monitoramento comum poderá facilitar a operação dos profissionais de saúde, na verificação dos parâmetros de operação de diversos ventiladores. Este projeto pode fazer a diferença no contexto da atual pandemia de COVID-19.
What We learned
Neste momento de distanciamento social, união sempre foi a palavra que nosso grupo buscou. Por esta razão, seguimos juntos neste desafio aprendendo a coordenar um projeto complexo a distância, utilizando de novas tecnologias para interagir entre nós e com o hardware que estávamos trabalhando. Foi preciso buscar conhecimento, aprender, se colocar à prova, e sempre muita união. Aprendemos que juntos, podemos transformar uma boa ideia em uma tecnologia aliada da população, da saúde e da economia.
Nesse desafio nós aprendemos a realizar um projeto de forma remota, não só o trabalho em equipe de forma remota, mas a parte experimental também.
Aprendemos a programar a aquisição e fazer o processamento de sinais do sensor de pressão. Foi necessário também estudar conceitos de fisiologia pulmonar para melhor entender os parâmetros de segurança.
What's next for Unified System for Artificial Ventilation Equipment (U-SAVE)
As propostas abaixo são destacadas como perspectivas futuras para o projeto:
Utilização de um sensor de oxigênio (como por exemplo: Galvanic oxygen sensor) para o monitoramento da mistura de oxigênio;
Uma válvula de segurança do AMBU, para garantir que o ventilador não exceda o limite;
Armazenamento dos dados para uma possível avaliação de problemas;
Permitir a configuração de mais valores de alarme como por exemplo, de PEEP e PIP, pelos profissionais de saúde de acordo com as necessidades de cada paciente;
Desenhar e imprimir um modelo em uma impressora 3D para servir de caixa para o monitor;
Testes de interferência eletromagnética;
Conseguir financiamento para produção em massa.
Built With
adafruit
arduino
c
Try it out
github.com | U-SAVE - Unified System for Artificial Ventilator Equipment | O Brasil precisa de ventiladores mecânicos, os ventiladores mecânicos precisam de nós. | ['Mateus Teixeira', 'Guilherme Ferreira Franco', 'Eric Kauati', 'carolina almeida', 'Michelle Mesquita', 'Lucas Lobianco De Matheo', 'Eder Oliveira de Souza'] | [] | ['adafruit', 'arduino', 'c'] | 45 |
9,914 | https://devpost.com/software/papure-2tpv60 | paPURE Setup - Angeled View - Utilizing Snorkeling Mask
paPURE Setup - Front View - Utilizing Snorkeling Mask
paPURE Setup - Side View - Utilizing Snorkeling Mask
paPURE Setup - Back View - Utilizing Snorkeling Mask
Original Prototype of paPURE Design View
paPURE Base - Top View - Inserted Compressor Fan and Fan Shroud
paPURE Base - Top View - Empty
Abstract:
The Filtrexa paPURE is an affordable, 3D printed powered air-purifying respirator (PAPR) that provides our healthcare providers with better protection than even N95s, especially in high-risk and confined environments (E.g. ICUs, ERs). It incorporates readily available components and can be easily manufactured locally. We can thus increase accessibility of PAPR technology by enabling hospitals to produce and purchase it as per their need, optimizing the 3D-print to produce it at a cost that is over ten times cheaper than PAPRs currently offered on the market, and using exchanging highly specific components for readily available and affordable components. The Filtrexa paPURE also has made design changes to improve comfort, ease of use, and longevity of PAPR technology.
Introduction
One of the most immediate and impactful effects of the COVID-19 pandemic are global shortages of proper personal protective equipment (PPE), forcing healthcare providers (HCPs) to consistently work in high-risk environments and unnecessarily place their own lives at risk. Our product is a powered air-purifying respirator (PAPR) that creates a positive pressure field with filtered air to protect frontline healthcare workers from airborne threats such as SARS, TB, measles, influenza, meningitis, and most immediately COVID-19. This technology improves upon current PAPR devices in terms of cost-efficacy, ease of access, and ease of implementability. Our solution not only serves to combat general PAPR shortages across the country, but also eases PPE shortages that arise from COVID-19 and future patient surges through an on-demand 3D printing process.
Value Proposition
Powered, air-purifying respirators (PAPRs) are currently the gold standard in medicine when treating patients diagnosed with COVID-19 and other highly infectious respiratory diseases[1] due to their positive pressure system. This system filters air extremely effectively before it reaches the airway. However, this technology package is costly, often totaling over $1800[2] and requires highly specific components which are currently in short supply. Both well-established hospitals such as the Mayo Clinic (with a ratio of 4500 physicians to 200 PAPRs)[2] and smaller county hospitals such as the Hunterdon Medical Center (where not a single PAPR is available to physicians) are facing critical shortages of personal protective equipment (PPE). Evidently, the aforementioned barriers render PAPR technology inaccessible to most frontline HCPs, leaving them far more vulnerable to infection.
Alternatives to PAPR technology include N95s, surgical masks, and currently, homemade masks due to a worldwide shortage of PPE. Although they provide a barrier against aerosols, standard and surgical N95s are easily compromised with an improper fit and have an assigned protection factor (APF) of ten[4], while PAPRs have an APF of 25 to 1000, rendering PAPRs far more effective at protecting HCPs. Additionally, physicians tend to prefer PAPRs over N95s because PAPRs are reusable, easier to breathe through, do not require fit testing, and make them feel safer[1][5].
Our Solution
In order to provide purified air to those in the most high-risk environments, we have developed a novel, inexpensive, and accessible PAPR device that is both lightweight and 3D-printable within 24 hours. Printed using readily-available filaments (e.g. PLA, ABS), paPURE is mounted to the user’s hip and assembled via on-hand motors and batteries. (See Appendix 2.5).
Through PAPR technology, HCPs are given access to filtered positive pressure air systems (in which airflow serves to seal any gaps in masks, as well as reduce respiratory fatigue in HCPs), drastically decreasing infection risk in areas such as ICUs and ERs.
Our device’s customizability allows for interoperability with existing masks, filters, and hosing (See Appendix 3.1), enabling hospitals, or possibly surrounding hobbyists/machinists (regulatory dependent), to produce PAPRs for their physicians and nurses. For images and procedures: See Appendix 1 and 2.
The system features a dual battery set-up that allows HCPs to utilize one or both batteries independently, as well as swap out batteries while the device is in use (such as during an extended patient procedure that a physician cannot leave from). Additionally the belt system, with the fan/chassis on you lumbar and 2 battery on ports on both hips gives a better weight distribution for improved comfort in extended usages (such as a surgeon leaning in an awkward position during the operation). The use of an inline filter means that air is pushed into a filter at the end of the device, as opposed to regular PAPRs that pull air through filters. This setup means that the risk of an imperfect seal compromising air quality is virtually nullified as no negative pressure system exists after air filtration in our device. Additionally, the aforementioned inline filters are better at filtering biological particles without disturbing airflow than standard P100s and are already used extensively in anesthesiology and respiratory care departments of hospitals across the country.
After printing the device’s chassis and shroud, integration with an inline bacterial/viral filter, housing, and masks will be followed by on-site fit and efficacy testing to ensure proper device assembly.[6] Then, an HCP would don their mask, clipping the paPURE chassis and two smart power tool batteries to a provided utility belt, and connecting to the mask via a hose. At most, we expect equipping paPURE to add 1-3 minutes to a medical professional’s routine and greatly improve safety and comfort.
An Improvement from Traditional PAPRs
Our technology eliminates the need for a middle-man manufacturer. Because the only required components are readily available to hospitals and clinics, hospitals can produce the device as per their need. We anticipate working with local 3D-printing facilities to produce and assemble the product, then to distribute the Filtrexa PAPR to hospitals. Physicians and NIOSH officials (most notably Richard Metzler, the first Director of the National Personal Protective Technology Laboratory at NIOSH), have already given us promising feedback regarding the need for this technology, and we are looking into potential partnerships with PPE developers and/or motor manufacturers. Some hospital purchasing experts have additionally communicated a need for affordable PAPRs. Our solution is over 10 times cheaper than current PAPR technologies ($155; see Appendix 2, Figure 2), increasing likelihood of adoption. To allow smaller hospitals to easily obtain our technology, we plan to raise awareness of our business through phone calls and emails to hospitals throughout the country.
Implementation Plan
paPURE’s solution is implementable almost immediately. The main barrier between our tested prototype and implementation is FDA/NIOSH approval (FDA EUA Sec II/IV Approve NIOSH Certified Respirators). We have also identified conditions that will allow us to expedite the regulation and roll-out of the production (such as the IDE and 501(k) pathways suggested to us by regulatory experts).[15] Because our device is based on existing PAPR technology, this predicate nature in combination with existing precedents for 3D-printed medical technology, can help expedite its deployment.[16]
Our technology minimizes the need for a middle-men. We are partnering with regional additive manufacturers to allow for quick, standardized, yet still decentralized production of the device. The only required components are readily available to hospitals and clinics, allowing HCPs to produce the device as per their need. Additionally, if regulatory approval permits, we may utilize local schools/universities/hospitals with on-site 3D printers in order to allow for fully decentralized manufacturing. After NIOSH Approval, our device (and depending on regulatory guidelines, possibly our CAD file) will be sent to those with 3D printers available, who could print and assemble the device (See Appendix 3.1).
Players involved in the production of this technology would be hospital assembly workers, but the design is easily assembled by anyone (the only limitation being that assembly be done under a fume hood to prevent contamination). Physicians we’ve already talked to have given us promising feedback regarding the need for this technology. We are currently looking into potential partnerships with PPE developers (See Appendix 3.2) and/or motor manufacturers. Our solution is over ten times cheaper than current PAPR technologies (See Appendix 3.3), increasing the likelihood of adoption.
Due especially to the length of this health crisis, hospitals are facing dire shortages of PPE. This has accelerated our timeline, but we are confident that it is feasible given the current state of emergency (See Appendix 3.4).
Since this product has yet to be implemented in hospitals, we are writing to you today to gauge your interest in paPURE. Additionally, any feedback you have relating to our product or interest in helping us with laboratory testing of paPURE would be greatly appreciated.
We anticipate our project to reach full fruition within 6-12 months. Our timeline is as follows. Our second iteration of prototyping for clinician testing will conclude in 2-3 weeks, followed by initial clinical testing, which will finish in around 1.5 months. As soon as clinical testing is finished and the product is validated, we will submit our product officially to NIOSH for regulatory approval. We anticipate receipt of regulatory approval within 1.5 months from submission. After approval is obtained, we will also apply for either a provisional patent or copyright, depending on legal advice. Within 1-2 months after regulatory approval, we plan to roll out our product to hospitals via centralized 3D-printing. During the next 1-2 months, we will continue to iterate and optimize the product. Official hospital rollout, with multiple 3D-printing partners and company partnerships, will occur around a month later. This will be around 6-7 months from now. As seen, our timeline is aggressive as we wish to equip healthcare providers with PPE as soon as possible. The prior goals mentioned in our timeline are our key goals and objectives for the project at this time.
Current Testing and Partnerships
Technical Testing is being carried out at Filrexa's primary residence and at Johns Hopkins University and includes analysis of airflow data, battery life, and filtration efficacy. For clinical testing, we already have established connections for clinical testing with both Johns Hopkins Medical Institute and Stanford University. In regards to business-focused assistance, we have also partnered with FastForwardU for advising regarding intellectual property protection, strategic marketing, and clinical networking.
Planned Partnerships
We plan to designate one 3D-printing company (current candidates include Xometry, Protolabs, Cowtown, and Health3D) as our manufacturer during our initial launch into the market, but will continue to partner with additional 3D-printing companies as our business grows. Due to our unique manufacturing approach, all hospitals, regardless of their size, will be able to order and quickly receive PAPRs, lowering the impact of the current shortage. In order to supply the auxiliary materials such as motors, batteries, and more, we plan to initiate company partnerships with large corporations such as 3M, Dyson, Black and Decker, GE, Cuisinart, Hitachi, Makita, Shop Vac, Hoover, Bissell, Shark, iRobot, and Bosch.
Additional Video
https://youtu.be/iFMtzt52BEQ
Appendix and Citations
Click here!
Website
paPURE Website
Built With
3dprinting
cad
cpap
p100 | paPURE | paPURE is a hospital accessible PAPR Technology utilizing 3D printing and readily available hardware to give healthcare's frontline the gold standard of personal protective equipment right now. | ['Sanjana Pesari', 'Hannah Yamagata', 'Sneha Batheja', 'Joshua Devier'] | ['2nd Place Overall Winners', '1st Place', 'The Wolfram Award', 'The Best Business Idea', '3rd Place Hack', 'Best COVID-19 Hack'] | ['3dprinting', 'cad', 'cpap', 'p100'] | 46 |
9,914 | https://devpost.com/software/qr-o-e-uma-plataforma-de-agendamento-de-entregas-a-domicilio | Ícone do nosso aplicativo (Logormarca)
Tela de inicio atual, onde o usuário se identifica como sendo o cliente que receberá a mercadoria ou o entregador
Se o cliente for selecionado esta tela e aberta para que ele informe sua ID
Assim que a ID é informada o código QR é gerado na tela do cliente e este deve ser apresentado ao entregador
Se o entregador for selecionado, a câmera do telefone do entregador é aberta possibilitando a leitura do código do cliente
Tela onde aparecerá o código QR gerado pelo cliente
Tela onde a câmera irá abrir para que o entregador escaneie o código do cliente
Carregamento do app concluído, aparece a tela onde o usuário se identifica
Caso selecione cliente, este deverá informar a sua ID
Se o entregador selecionar a tela de cadastro, ele devera preencher os campos necessários e concluir o cadastro
Após clicar no ícone do aplicativo deverá aparecer esta tela
Caso selecione entregador, este deverá efetuar o seu login, se o entregador não possuir um cadastro ele pode selecionar a opção de cadastro
Inspiration
Somos dois no grupo com experiência com o trabalho de entregas, no Rio de Janeiro e em São Paulo, os centros que mais carecem e oferecem este serviço. E todos nós também já recebemos em casa encomendas entregues por estes tantos meninos e meninas que transportam o mundo sobre 2 rodas. Eles são invisíveis até que se pense que podem trazer e levar o Corona Vírus em seus Gadgets. É responsabilidade de todos nós cuidarmos para que estas pessoas possam trabalhar sem se expor a riscos.
Em tempos de isolamento social cresceu a demanda pelas entregas à domicílio e também o número de pessoas que, desempregadas, migraram para a informalidade do mercado de entregas. Muitos realizam estas entregas utilizando a bicicleta e nosso desafio engloba uma solução voltada para elas.
A ideia de uma plataforma de agendamento de entregas voltada para a área de ciclo logística é urgente, uma vez que os grandes centros carecem de soluções de logística sustentável, diminuindo a emissão de poluentes, mas também uma solução que se preocupe em valorizar financeiramente o trabalho dos profissionais que atuem no ramo, motivando a inclusão social deste público. Não é condizente querer um mundo menos poluído excluindo do reconhecimento por esta luta quem utiliza a bicicleta para realizar as entregas.
A preocupação com o risco de contágio envolvendo clientes e entregadores nos fez perceber que o uso da tecnologia do QR-Code é a mais eficaz para este fim, uma vez que garante que a entrega aconteça sem o risco de contágio, pois elimina o contato de ambos os envolvidos no processo de validação e cerificação da identificação do receptor da entrega.
What it does
O cliente emissor acessa a plataforma de entregas "QR-o" na web, preenche o cadastro, informa os dados de coleta e entrega, volume e peso. O valor do frete é calculado e a entrega é agendada pelo cliente emissor, que paga através do paypal pelo serviço.
Na data escolhida, a plataforma, conectada ao aplicativo de entrega, rastreia e identifica entregador mais próximo ao ponto de coleta.
Para este entregador é informado o valor pago pela entrega e a distância a ser percorrida, e ele decide se aceita ou não a "pedalada". Ao aceitar, seu ID de entregador é enviado para o cliente emissor, que confirma este ID ao contactar o entregador.
Ao chegar ao destino da entrega, o cliente recebedor é informado e se apresenta com o dispositivo móvel com o código QR-Code recebido. O entregador valida a entrega da encomenda através da leitura do QR-code e finaliza o processo.
How I built it
Este aplicativo foi construído utilizando o Android Studio e servidores Apache para criação de um aplicativo que atualize todos seus usuários acerca da validade do código QR de cada cliente e da geração de novos.
Challenges I ran into
Na parte do design os maiores desafios foram conseguir passar para o usuário a nossa mensagem, transmitir nossa ideia de sustentabilidade, de inovação, segurança e mobilidade, tudo isso sendo representado em uma simples logomarca. Na parte de design das telas do aplicativo, o desafio foi fazer algo que seja visualmente agradável e ao mesmo tempo intuitivo, sem muitas informações desnecessárias e/ou imagens.
Na parte de desenvolvimento os desafios mais presentes foram utilizar o PHP de modo que complementasse a tecnologia android, além de implementar a UI. De modo geral, o grande desafio foi usar essas tecnologias diferentes de forma harmônica.
Accomplishments that I'm proud of
Embora seja apenas o rascunho do nosso projeto e ele ainda esteja bem primitivo, nós nos orgulhamos de conseguir desenvolve-lo no geral, temos orgulho do nosso aplicativo, da nossa ideia e de conseguirmos desenvolver o principal em um prazo curto.
What I learned
Ambos conseguimos aprender um pouco mais sobre as tecnologias usadas para o desenvolvimento do app, conseguimos adquirir mais experiência e conhecimento nessa parte de desenvolvimento mobile.
What's next for
Estamos mais do que dispostos a levar o projeto adiante, queremos editar o visual do nosso aplicativo, acrescentar um tela de cadastro para os entregadores, fazer a construção da parte web, que seria responsável pela comunicação com o cliente emissor (o que possui a mercadoria para entrega) e consertar possíveis erros da versão inicial.
Built With
android-studio;
apache;
java;
php;
Try it out
github.com | QR-O | QR-o (Quero) é a plataforma de agendamento de entregas à domicílio, que utiliza a tecnologia do QR-code garantindo que a entrega seja realizada sem risco de contágio de clientes e entregadores. | ['Eduardo Nery', 'Pedro Luan Albuquerque Pinto'] | [] | ['android-studio;', 'apache;', 'java;', 'php;'] | 47 |
9,914 | https://devpost.com/software/wecare-5l9dgi | Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Map Screen of app, which allows you to see hotspots around you and your Care Circle.
Care Circle screen of app, which allows you to health conditions of your loved ones.
Web interface, which can be used to update the symptoms. It is synced with the app.
New logo.
Update with a key.
Hotspots for countries.
Options from the start.
Questions about your health.
Hot spots.
App design
As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g.,
UK app
), contact tracing (e.g.,
PPEP-PT
), and environmental risk dashboards (
covidmap
). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Unless being mandatory, we did not observe the large-scale adoption of these technologies by the crowd. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources.
Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities.
WeCare Solution
WeCare is a cross-platform app that enables you to track the health status of your loved ones. Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates on best prevention practices. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data.
WeCare includes a contact tracing module that follows the guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing
(PEPP-PT)
. It is an international collaboration of top European universities and research institutes to ensure the safety and privacy of individuals.
What we have done during the weekend
Have been in contact with other channels in Brazil and Chile.
We have updated the pitch (extended), app-design and backend connection of the app this week. New contacts with Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn. We have also modified the concept of Care Circle and how to add/remove individuals. Now, the app is very easy-to-use with minimal input (less than a minute per day) from the user. We are proud of the achievements of our team, given the very limited time and all the challenges.
Challenges we ran into
The Hackathon brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools.
Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information.
In the development of a live hotspot map, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models.
Also for the testing of the iOS version, we ran to the new restriction of App Store for COVID-related apps, which should be backed up by some health authorities or governmental entities.
The solution’s impact on the crisis
We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today.
The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries.
The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices.
Thereby, WeCare enables everyone to make important contributions toward addressing the crisis.
Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions.
The necessities to continue the project
We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings:
Public support: a partnership with authorities and potentially being a part of government services to be able to deploy it on AppStore. It also makes WeCare more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis.
Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities.
Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run.
The value of your solution(s) after the crisis
The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu).
Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis.
The URL to the prototype
We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our
Website
.
Github repo
.
Pitch:
https://youtu.be/7fMrVqxoPKY
Pitch extended version:
https://youtu.be/Vo0gs3WlptU
Other channels.
https://www.facebook.com/wecareteamsweden
https://www.instagram.com/wecare_team
https://www.linkedin.com/company/42699280
https://youtu.be/_4wAGCkwInw
(new app demo 2020-05)
Interview:
https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app
Built With
node.js
python
react
vue.js
Try it out
www.covidmap.se
github.com | WeCare | WeCare is a privacy-preserving app & page that keeps you & your family safer. You can track the health status of your cared ones & use a live hotspot map to start your normal life while staying safer. | ['Alex Zinenko', 'Sina Molavipour', 'Ania Johansson', 'Hossein S. Ghadikolaei', 'Christian M', 'Seunghoon HAN', 'Tomasz Przybyłek', 'Mohamed Hany', 'Alireza Mehrsina'] | ['1st Place Overall Winners', '2nd Place'] | ['node.js', 'python', 'react', 'vue.js'] | 48 |
9,914 | https://devpost.com/software/algoritmo-para-teste-assintomaticos-e-anticorpos | Inspiration, salvar vidas.
What it does, algoritmo analisa dados e identifica assintomáticos, anticorpos e pacientes sem vírus.
How I built it, programação básica de software.
Challenges I ran into, desenvolver o código fonte e trabalhar com dados de Entrada de outros sistemas.
Accomplishments that I'm proud of poder ajudar a população com esse desenvolvimento.
What I learned, que não há limites quando queremos ajudar.
What's next for Algoritmo para teste assintomáticos e anticorpos, desenvolver o código e integrar aos sistemas de testes.
Built With
c++
statement
visual-basic | Algoritmo para teste assintomáticos e anticorpos | A ideia é disponibilizar um algoritmo para identificar e separar assintomáticos de pacientes sem vírus e ainda utilizar pacientes com anticorpos | ['Robson Alberis Soares da Silva'] | [] | ['c++', 'statement', 'visual-basic'] | 49 |
9,914 | https://devpost.com/software/xo-corona-desinfetante-de-compras-zc57tb | Inspiração
Muitas pessoas não entendem os riscos de transmissão por superfícies contaminadas e não dão atenção à higienização das compras, por ser um processo trabalhoso...
O que ele faz
Automatiza o processo de desinfecção das compras, tornando-o menos trabalhoso. Desinfeta os alimentos e suas embalagens, inativando não só o Sars-Cov-2, mas também vários outros patógenos que possam estar impregnados.
Deixa você e sua família mais seguros, com a certeza de que a COVID-19 não será adquirida como um brinde na compra de uma maçã.
Construção
Desafios
Conquistas
Aprendizado
Próximos passos
Built With
arduino | Xô Corona - Higienizador de compras | O Xô Corona é um higienizador de compras automatizado e visa combater a entrada do SarsCov2 em residências | ['Derlei Silva'] | [] | ['arduino'] | 50 |
9,914 | https://devpost.com/software/c-trac-app-for-tracking-corona-hotspots | Inspiration
During this current COVID 19 pandemic, I see health worker is curing the patients, doctors are innovating new medicine, the police is controlling the crowd movement and even bus drivers are helping people to get back to home. As a future engineer, I felt like my contribution is none, so I felt motivated to do my part and try to bring a positive change and to make sure my product can also be used in a future pandemic.
problem our project solves
we all can agree that this pandemic needs to overs soon so as we can meet our loved ones, in order to contain this pandemic, the government is using CONTACT TRACING APPS ( CTAs ). Research says if contact tracing is done correctly it can reduce the number of case 3 folds, then why the number is still rising? , the problem with these CTAs is they only tell whether you have come in contact with an infected person or not, what it doesn't tell us that from where the person caught the infection ( the parent source ). let's take an example if there are two-person 'X' and 'Y' and Y got infected then X will get notified by the current CTAs that he might have got an infection as he came in contact with Y, but it doesn't tell from Which PLACE y got the infection, this is crucial as if we don,t find out that PLACE then many other people who had visited that PLACE may get the infection.
what our project does
Our project C-TRACK 1st of it's kind of reverse contact tracing app, so let me explain how Reverse contact tracing works, whenever the user visits a place too frequently like a shopping mall. then that particular location will be saved inside the app and if in future user found COVID +ve then we can track down that shopping mall, the app will also send a notification to all over people who have visited that exact shopping mall, now health authorities can sanitize and lockdown that specific shopping mall instead of locking down the whole locality. the location stored is fully encrypted and can only be accessed by the user. it also has two additional feature
1.) it sends 'wear mask ' notification when the user leaves then house and 'wash hand' notification when the user returns the house, this small precaution can bring a huge change by keeping you and everyone around you safe.
2.) whenever the user enters a government certificated hotspot or RedZone he will get a warning notification
Challenges I ran into
1,) we lack financial support as we have to make this app from scratch.
2.) the problem in collecting data regarding government-certified hotspot and also we have to do a lot of research regarding the spread pattern of COVID-19.
3.) It was hard for us to get in contact with health workers as they were busy fighting an increasing number of patients so we have to talk to retired doctors.
4.) It took us too long to use it in real-time as during lockdown it was too hard to go outside in the quarantine but finally, after lockdown loosens a bit we tested it and it gave an excellent result.
What I learned
All team members of C-TRACK were able to grow their area of competence by participating in the whole process of idea definition, market research, validation, prototyping, and presentation. Through different mentor sessions, we learned that problems could be approached by many means, but most importantly our mission should be clear.
What's next for C - TRAC App for tracking corona hotspots
our app can be used for a future pandemic or seasonal diseases such as swine flu or bird flu.
Built With
android
android-studio
java | C - TRACK 1st ever reverse contact tracing App | Our app is 1st reverse contact tracing app which locate the possible hotspots from the user location history and also 1st safety awareness system which notify user to ( wear mask ) and ( wash hand). | ['Anup Paikaray', 'Arnab Paikaray'] | [] | ['android', 'android-studio', 'java'] | 51 |
9,914 | https://devpost.com/software/lixo-seguro-ou-residuo-biologico-seguro-h2yos3 | GIF
Saco de lixo seguro
Inspiration
A ideia dessa temática e de realizar o projeto LIXO SEGURO OU RESÍDUO BIOLÓGICO SEGURO foi inspirada de uma situação crítica e perigosa que a população mundial e a brasileira estão passando, nesse momento atual, com a pandemia de CORONAVÍRUS.
Observa-se nos noticiários e nas praticas e ações dos gestores municipais, estaduais e federais a ausência de ações concretas de proteção à saúde dos trabalhadores que fazem coleta de lixo urbano.
Essa situação é preocupante, haja vista que que esses trabalhadores já vivem no seu cotidiano em isolamento social, por serem discriminados e não terem acesso aos itens básicos das políticas públicas.
What it does
A utilização de sacos padronizados, por esses trabalhadores, pode ser considerada uma barreira de proteção à saúde.
Os sacos serão distribuídos para esses trabalhadores acondicionarem o lixo que estão em sacos, na porta das residencias ou em coletores em pontos estratégicos.
How I built it
Essa construção foi pensada e imaginada em uma ferramenta mais fácil de ser confeccionada e de uso por esses trabalhadores. Então, um saco padronizado, cor chamativa e com o simbolo do vírus, atenderia a proposta, bem como a sua finalidade.
Challenges I ran into
Não posso afirmar que tivemos dificuldade, já que o projeto é simples, mas, potencialmente, eficaz para o proposito. Ele é economicamente viável, se comparado com os gastos financeiros hospitalares e as perdas de vidas; socialmente justo, ecologicamente correto e será aceito pela saúde coletiva.
Accomplishments that I'm proud of
As conquista desse projeto podem ser destacadas: aprendizado coletivo, pessoas pensantes para o bem comum, uso dessas ferramentas digitais, desconhecidas e a partir, desse momento, poderá ser mais familiarizadas, contatos com hackers e outros mentores.
What I learned
Aprendi que a tecnologia não anda sem o calor humano presente. Então, ambos se complementam.
What's next for LIXO SEGURO OU RESÍDUO BIOLÓGICO SEGURO
Verificar a possibilidade de aproximação com os gestores, para que esse projeto seja acolhido, em beneficio dos trabalhadores da coleta de lixo , urbano e do meio ambiente.
Built With
poweponit | LIXO SEGURO OU RESÍDUO BIOLÓGICO SEGURO | O lixo gerado nas residências, esta com o CORONAVIRUS os trabalhadores da coleta de lixo urbano, está em risco.A distribuição de sacos padronizados preserva à saúde desses trabalhadores. | ['WÉLTIMA CUNHA'] | [] | ['poweponit'] | 52 |
9,914 | https://devpost.com/software/havkcovid19-ventilador-pulmonar-vp | Engenharia Arquitetura Sistema Vantiador Pulmonar
Overview
Diagrama de Blocos
Diagrama de Blocos
Função Arquitetura
Forma
Decisão
Decisão
Decisão
Controle Ventilador Pulmonar
Componentes
Inspiration Salvar Vidas
What it does Controle de Ventilador Pulmonar
How I built it Através de devices e peças de mercado como PLC, IHM, Stacklight (coluna luminosa), e possibilidades de usar integrado IHM+PLC.
Challenges I ran into É buscar hardware de controle e Corretos devices que atenda nosso projeto para construção rápida de protótipo para colocar em operação.
Accomplishments that I'm proud of através desse projeto disponibilizar meu conhecimento para desenvolver e projetar um equipamento tão difícil hoje em dia para lutar contra nosso maior inimigo, o covid19.
What I learned que não há obstáculos para seguir em frente e iniciar o projeto para programação do software plc e IHM para fabricação do ventilador.
What's next for Havkcovid19 Ventilador Pulmonar (VP). Próximos passos será colocar em operação e disponibilizar para fabricantes poderem pegar e utilizar do template.
Built With
ihm
ihmc-cmap
ladder
plc
rockwell
siemens
tia-portal
valvulas
wincc | Havkcovid19 Ventilador Pulmonar (VP) | A ideia é fazer um software template para ser usado em diversos hardwares de mercado como plc e ihm. | ['Robson Alberis Soares da Silva'] | [] | ['ihm', 'ihmc-cmap', 'ladder', 'plc', 'rockwell', 'siemens', 'tia-portal', 'valvulas', 'wincc'] | 53 |
9,914 | https://devpost.com/software/esterilizacao-utilizando-radiacao-ultra-violeta | Quebra do RNA de micro-organismos
Incidência de UV na pele
Onde a Ultravioleta age no micro-organismo
Uma lâmpada ultravioleta
Um dos fatores impactantes na saúde é a contaminação pela manipulação mesmo que involuntária de objetos e alimentos e virus e bactérias em suspensão no ar em ambientes enclausurados.
O objetivo do projeto é realizar de forma eficaz e rápida a esterilização neutralizando o covid19 nas superfícies de objetos , alimentos incluindo a esterilização de água para consumo e outros fins e ambientes controlados, corredores onde circulam pessoas, veículos principalmente ambulâncias que precisam ter ar condicionado em certas circunstâncias..
A elaboração do primeiro protótipo se fez com uma lâmpada ultravioleta em um gabinete fechado , o que impedia o vazamento dos raios.
Um dos desafios foi a correta forma de disponibilizar os raios ultravioleta de forma a atingir o objeto a ser esterilizado com a distancia correta e potencia adequada, e manter o procedimento seguro.
Realizar um projeto que promova uma proteção a saúde e segurança, traz satisfação.
Através deste projeto, foi possível verificar que estudos podem promover tecnologias que beneficiam a todos.
As próximas etapas do projeto são verificar as disposições, quantidades e treinamentos para utilização do processo de esterilização por radiação ultravioleta.
Built With
lamp
lampadas
ultravioleta
ventilacao | Esterilização utilizando radiação ultra violeta | Esterilização de forma rápida em ambientes, objetos, alimentos de forma segura e sem alteração de características. | ['André Luiz Menezes Pereira', 'Ricardo Santos', 'Lucas Melo'] | [] | ['lamp', 'lampadas', 'ultravioleta', 'ventilacao'] | 54 |
9,914 | https://devpost.com/software/todomundo-893l5n | Logo do aplicativo
Animação para carregar a troca de tela se for preciso
Boas vindas ao aplicativo
Criar uma nova conta ou logar no aplicativo
Criar perfil caso não tenha conta no aplicativo
Separando o perfil do profissional da saúde
Começo da coleta de dados - Nome
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Home do usuário com as opções de funcionalidades que ele vai encontrar no aplicativo
Funcionalidade Farmácias - usuário vai informar o remédio que precisa e nós vamos apontar a farmácia mais próxima que tenha a medicação
Criar uma senha
Funcionalidade para o Farmacêutico - indicar o seu estoque de medicações para indicarmos pro usuário onde ele pode localizar esse remédio
Funcionalidade Hospitais mais próximo - aqui vamos apontar o hospital/UBS mais próxima contendo informações como leitos disponíveis e afins
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Coleta de informações do usuário - autoavaliação para criar indicadores do dashboard tanto para profissional da saúde como o próprio usuário
Ilustração da forma de exibição do dashboard
Ilustração da forma de exibição do dashboard
Inspiration:
A equipe Gruve percebeu que as informações dos dados sobre COVID ou qualquer outra doença estão bem dispersas em aplicativos ou até mesmo em páginas do governo, sus e afins, com isso tomamos como inspiração o desafio de centralizar esses dados para transformar o modo como as pessoas se relacionam com a saúde da população, disponibilizando informações em tempo real em forma de indicadores para os profissionais da saúde.
Link do storytelling do produto
:
https://bit.ly/2Z93YMY
What it does:
O
todomundo
tem a função de absorver as informações que o nosso usuário vai informar por meio da autoavaliação diária da sua saúde e com essas informações alimentar uma base de dados que por sua vez tem a finalidade de ser um dashboard para os profissionais da saúde com indicadores que mapeamos que são necessários por meio de entrevistas com médicos, farmacêuticos, enfermeiras e etc, e outro dashboard com a visão do usuário para fins de pesquisa em relação a como está o bairro dele em relações a sintomas detectados por exemplo.
How we built it:
Estamos construindo essa solução com o uso de React e css3 para o front-end, sql server para armazenar as informações dos usuários, .net para o back-end e python para analise de dados.
Challenges we ran into:
Criar uma forma de engajamento para o usuário continuar utilizando o aplicativo diariamente, encontrar uma forma de centralizar as informações, como falamos, existem dados, mas não são de fácil entendimento ou até mesmo uso para pesquisas.
Accomplishments that we're proud of:
A equipe Gruve tem o orgulho de dizer que após horas de trabalho e levantamento de pesquisas com pessoas conseguimos idealizar um produto que fechasse toda as questões que fomos levantando ao longo desses dias. Nossa dashboard não está focada somente aos sintomas de COVID, fazendo então com que nossa aplicação tenha uso até mesmo pós pandemia.
What we learned:
Aprendemos que o trabalho em equipe e a junção de muitas ideias são fundamentais para mudar o cenário atual do mundo em que vivemos. Encontramos dificuldades no meio do caminho, mas se não fosse a ajuda dos ativadores, mentores e amigos é capaz que nem aqui estaríamos.
Vimos que quanto mais informação de qualidade chegar aos profissionais, mais sucesso podemos obter em busca de remédios, prevenções e tudo o que for preciso.
Mas se for pra deixar um grande aprendizado, podemos falar que nunca estamos sozinhos, se o assunto for melhorar o mundo onde moramos acredite, sempre vai ter alguém para te ajudar.
What's next for todomundo:
Próximas etapas, concretizar o desenvolvimento(programação) do aplicativo para lançamento.
Conversas com hospitais, SUS e afins para entender como funciona o processo de preenchimento das informações como quantidade de pessoas doente no hospital, quantidade de óbitos e recuperados, tudo isso para deixar o aplicativo ainda mais robusto e funcional para nossos profissionais da saúde.
Built With
.net
css3
python
react
sql
Try it out
xd.adobe.com | todomundo | Transformar o modo como as pessoas se relacionam com a saúde da população, disponibilizando informações em tempo real em forma de indicadores para os profissionais da saúde. | ['hassany chaves', 'Brenda Xavier', 'izzadora Bastos de Sá Barreto', 'Davi Dallapicola'] | [] | ['.net', 'css3', 'python', 'react', 'sql'] | 55 |
9,914 | https://devpost.com/software/yocie-sua-amiga-e-professora-virtual | PROBLEMA A SER RESOLVIDO (#D126, #D041):
Muitos alunos estão com dificuldades para estudar em casa nesse momento de quarentena, assim como muitos professores querem ajudar mas não sabem como. Este período de isolamento evidenciou também uma dificuldade dos familiares em dar suporte educacional aos estudantes, principalmente do ensino fundamental e médio.
DESCRIÇÃO:
Yocie é uma professora virtual baseada em inteligência artificial que ajuda alunos a buscarem conteúdos e solucionarem dúvidas sobre determinados assuntos, via WhatsApp chatbot. Além disso, Yocie também pode conectar o WhastApp esses alunos aos tutores voluntários cadastrados na nossa base de dados.
SOLUÇÃO PROPOSTA:
Proposta de simples implementação e com potencial de amplo acesso, visto que a difusão do WhatsApp como rede social no Brasil é ampla. Além disso, o baixo consumo de dados do aplicativo que muitas vezes estão inclusos nos contratos das telefonias móveis (isto é, são ilimitados), torna a Yocie uma assistente de estudos de amplo acesso mesmo com problemas de limitação de internet. Yocie promoverá uma primeira interatividade com o aluno, irá processar a dúvida, pesquisar online, e direcionar conteúdo ao aluno, principalmente textos e imagens, que possui baixo consumo de dados móveis. Caso o aluno não possua dados móveis mas possua um acesso ilimitado ao whatsapp, ele terá uma ótima oportunidade de buscar conteúdo online com a ajuda da Yocie.
PARCEIROS E RECURSOS NECESSÁRIOS:
A implementação do sistema será através da linguagem de programação Python, a partir das ferramentas Flask, Selenium, Twilio e Mongodb. Existe também a opção de implementação via WhatsApp Business API, mas requer um cadastro de empresa de pequena/médio porte, com cobrança de cerca de 2 centavos por mensagem respondida, após 24 horas de conversa. A opção via Twilio é de mais rápida implementação e possui uma cobrança de cerca de 3 centavos por mensagem respondida do chatbot. Seria possível buscar uma parceria com o Whatsapp e com o Twilio para isenção desta taxa visto que a proposta não possui fins lucrativos e é desenhada para auxiliar, de modo emergencial, alunos com dificuldade para estudar em casa neste período da quarentena. O servidor da Yocie será sediado no Google Cloud.
RISCOS:
Os principais riscos estão associados à estratégia de marketing adotada para atingir os alunos que mais precisam da plataforma e à baixa aderência de 'tutores voluntários'. Porém, um sistema de pontuação para estimular participação com benefícios provenientes de empresas parceiras podem ajudar a minimizar esses riscos.
IMPACTO PARA A SOCIEDADE (ABRANGÊNCIA):
A proposta é desenhada para abranger a população que possui acesso ao WhatsApp, uma ferramenta com baixo consumo de dados. Em 2017, 56% da população brasileira fazia uso do WhatsApp, e a projeção para 2019 era de ter 77 milhões de usuários no Brasil, onde 61% da população faz uso de internet móvel e 98% dos usuários de smartphones utilizam o WhatsApp diariamente (
https://www.messengerpeople.com/pt-br/whatsapp-no-brasil/
). Deste modo, a solução via WhatsApp apresenta um forte potencial de atingir rapidamente o público alvo.
O Brasil também apresenta o 4º maior crescimento do número de dispositivos móveis do mundo (
https://www.messengerpeople.com/pt-br/whatsapp-no-brasil/
), indicando um mercado em expansão, com cada vez mais pessoas em potencial para utilizar a ajuda da Yocie.
Inicialmente, a abrangência é nacional, mas com potencial de expansão para outras línguas.
VIABILIDADE DE IMPLANTAÇÃO (TIMING):
Se for escolhida a implementação via Twilio, é estimado um timing de 2 semanas, caso seja escolhida a implementação via WhastApp Business API, que teria menos custos, seria difícil estimar um tempo devido a necessidade de aprovação da empresa. O timing também pode ser afetado pela negociação com os parceiros.
EQUIPE
A equipe desenvolvedora do projeto até o momento é formada por duas pessoas, ambos integrantes do Clube do Cientista, um projeto em forma de comunidade que desenvolve e aplica metodologias educacionais baseada em ciência e tecnologia. A inteligência artificial da Yocie deverá ser aprimorada com o tempo com apoio teórico de pedagogos, educadores e professores, em uma forma de comunidade de colaboração com o projeto, sendo integrantes do Clube do Cientista ou não.
CONTATOS
website ->
https://www.clubedocientista.com/
linktree ->
https://linktr.ee/clubedocientista
instagram ->
https://www.instagram.com/clubedocientista/
emails:
Clube do Cientista ->
clubedocientista@gmail.com
Fábio ->
fabiofcx@gmail.com
Rafael ->
rafagmenezes@gmail.com
Built With
flask
google-cloud
mongodb
python
selenium
twilio
whatsapp | Yocie - Professora virtual! | Yocie é uma professora virtual que ajuda alunos a solucionarem dúvidas sobre determinados assuntos, via WhatsApp chatbot. Yocie também pode conectar os alunos aos tutores voluntários cadastrados. | ['Fabio Contrera', 'Rafael Menezes'] | [] | ['flask', 'google-cloud', 'mongodb', 'python', 'selenium', 'twilio', 'whatsapp'] | 56 |
9,914 | https://devpost.com/software/sivep-digital | Logo.
Tela de login implementada.
Modelo atual das janeles de preenchimento.
Inspiration
The inspiration for the project in centered in the social context.
This pandemic made all of us feel impotent and insecure, but the HackCovid and the Sivep Digital project gave us a way to contribuit with what we know to help in the best possible way in this context.
What it Does
Sivep Digital is an app, initially for Desktop, where the health professionals will be able to fill the Sivep record, already updated for Sars-Cov-2. Besides that, Sivep Digital makes it possible and easier for data collection and processing, once it creates a database for the submited record.
How I Build It
The app was mainly created with Python programming language, using Tkinter library for the graphical interface and Sqlite3 for the database management. The statistical analyzes have been made using the Pandas library and the graphics plots used the Matplotlib library.
The group used Pycharm Community Edition and VSCode as code editors and the Github as remote repository.
Challenges I ran into
The team is consisted of five physics students, wich means that interface programming is not usual for the group. Considering this, a great challange dealt was learn how to manage a graphic interface. Another great challenge was the learning of how to create and manage the SQLite3 library tools and SQL data bases.
Accomplishments that I'm proud of
The team is most proud of the creative solutions that we have created in the process, and, of course, the help we provide to the health institutions and the health professionals in this pandemic context.
What I Learned
All of us had learned a lot in the process, specially about the librarys and the data management.
What's Next for Sivep Digital
The first thing that the team would like to implement is an automatic fill of the address fields with the CEP entry, in addition to the possibility of taking it to mobile devices. The program is quite versatile in this sense, since it is written in phyton, a language whose wealth of tools and versatility are massive.
Built With
github
matlib
pandas
pycharm
python
sqlite
tkinter
vscode
Try it out
github.com | Projeto - Sivep Digital | The most dynamic and practice way for record filing and data management. | ['Mateus Corradini Lopes', 'João Victor Machado Barboza', 'Ian Lima Santana', 'João Rheinheimer', 'Reinaldo Martins'] | [] | ['github', 'matlib', 'pandas', 'pycharm', 'python', 'sqlite', 'tkinter', 'vscode'] | 57 |
9,914 | https://devpost.com/software/d0007-path-to-emergence | Significado do Nome do Projeto
Scora Dashboard - Predição da Taxa de Ocupação por Unidade Hospitalar
Inspiration
Uns dos principais desafios na jornada de combate ao coronavírus é a intensa demanda exercida sobre o sistema de saúde por pacientes suspeitos ou confirmados com a COVID-19. Usando práticas de gestão de operações, previsão de demanda e nivelamento da produção, nós da Scora desenvolvemos uma solução que, além de otimizar a gestão da capacidade instalada em hospitais superlotados, também direciona pacientes para as unidades de atendimento mais próximas com as menores taxas de ocupação.
What it does
Nossa proposta é utilizar dados reais de atendimentos a pacientes de coronavírus e número de leitos hospitalares para calcular a taxa de ocupação e prever sua evolução para os próximos 7 dias.
Diferente de outros serviços que disponibilizam a informação de covid por bairros ou municípios, disponiblizamos a taxa de ocupação por unidade hospitalar.
Disponibilizamos um dashboard com gráficos de internação de novos pacientes, tempo de internação por tipo de evolução clínica (cura ou óbito), e número de leitos ocupados e disponíveis por tipo (com ou sem respiradores). Todas essas informações podem ser visualizadas por unidade de atendimento ou por diversas unidades de uma mesma região sobrepostas, possibilitando a gestão individual e coletiva das taxas de ocupação.
Há ainda uma funcionalidade específica para o cidadão que busca por atendimento: o app é capaz de informar as unidades de saúde mais próximas de sua localização, com dados de taxa de ocupação, data de atualização dessa taxa, horário de atendimento, formas de contato e recomendar o melhor hospital. Tudo isso a fim de promover maior rapidez e conforto ao usuário na busca por atendimento.
How I built it
A ferramenta é construída utilizando dados de ocupação de leitos e séries temporais com as demandas hospitalares. Nossos cálculos são baseados em atributos de idade, bairro, tempo de permanência, evolução do caso, entre outros. Desta forma, utilizamos algoritmos de aprendizado de máquina baseados em redes neurais para detectar padrões e realizar predições da taxa de ocupação futura.
Challenges I ran into
O principal obstáculo no desenvolvimento do app foi a obtenção de bases de dados, atualizadas e contendo os atributos relevantes para a construção modelo. Apesar de existirem algumas bases de dados sobre o atendimento de pacientes da covid-19, a maioria apresenta os números agregadas por região ou bairro, e não por unidade de saúde. As poucas bases por hospital encontradas apresentam dados que são atualizados mensalmente, o que dificulta a tarefa.
Accomplishments that I'm proud of
Temos particular orgulho da nossa modelagem para previsão da taxa de ocupação. Ao invés de tentarmos prever a demanda por novos leitos (entradas) e as curvas de evolução clínica e liberação de leitos (saídas), como seria intuitivo, mas extremamente complexo, percebemos que a informação mais relevante a ser prevista é a variação na ocupação dos leitos (ou seja a diferença entre entradas e saídas a cada dia). Isso possibilitou que a modelagem matemática fosse aproximada ao problema do nível de água na caixa d’água, mais simples de desenvolver uma vez que contém somente uma variável dependente (a taxa de ocupação) que é definida por variáveis independentes existentes em bases de dados reais (entradas e saídas).
What I learned
Aprendemos que o isolamento imposto pelo coronavirus não nos impede de nos unirmos para desenvolver soluções para vencer a covid-19. Somos uma equipe multidisciplinar, formada por pessoas de diferentes Estados, e soubemos usar a criatividade e ferramentas de colaboração para juntos desenvolvermos uma solução que seria impossível de criarmos sozinhos. Por este projeto, descobrimos diferente bases de dados e tivemos dimensão do difuculdade de gerar informação neste âmbito.
What's next for Scora
Neste MVP 1, utilizamos dados públicos atualizados até o dia 15 de maio, mas o governo do Rio de Janeiro já demonstrou que deve tornar público dados sobre leitos para Covid-19, que serão atualizado em tempo real (1). Portanto, nosso próximo desafio é integrar a solução à base de dados governamentais e em futuros desenvolvimentos expandir esta solução para outros estados, disponibilizando esta informação, com qualidade, para outras unidades de saúde. Demos um passo pequeno no município do Rio de Janeiro, mas nossa meta é abranger o Brasil.
Além da expansão territorial, nossa solução pode ser ampliada para outros recursos escassos no combate ao coronavirus. Disponibilidade de respiradores, equipe médica, testes clínicos, entre outros insumos que precisam ser cuidadosamente gerenciados. Além disso, nossa proposta claramente pode ser adaptada para outras doenças epidemiológicas, como dengue, zika, dentre outras.
(1)
https://veja.abril.com.br/brasil/rio-de-janeiro-deve-tornar-publico-dados-sobre-leitos-para-covid-19/
Built With
figma
keras
pandas
python
tensorflow
Try it out
github.com | Scora | Nosso aplicativo recomenda as unidades de saúde mais próximas com leitos disponíveis e estima a taxa de ocupação futura de leitos por unidade de saúde para fins de gestão. | ['Lino Guimarães Marujo', 'Kaio Tsuruta Gomes', 'Anne Teixeira', 'Luis Felipe Müller de Oliveira Henriques', 'Felipe Scandiuzzi', 'Rafael Rocha', 'Paulo S. Hollaender', 'Mateus Cabral', 'Eduardo Bucker', 'Mariana Betine'] | [] | ['figma', 'keras', 'pandas', 'python', 'tensorflow'] | 58 |
9,914 | https://devpost.com/software/ead-em-uma-intranet-falta-equipe-e-nome | Inspiração
Levar a educação para todas pessoas
Qual a solução
Disponibilizar uma rede Wi-Fi que possibilita acesso aos conteúdos do próprio servidor. Um sistema com EAD que pode ser usado por aplicativos ou navegado no próprio sistema web.
Como é feito
Com desenvolvimento de API em Node. Um ambiente "admin" para cadastrar os conteúdos.
Um backend em Node ou Python para puxar os vídeos do Youtube em uma pasta.
Este conteúdo que será preparado e importado para o sistema EAD no equipamento Wi-Fi.
Este equipamento já existe, de uma startup (temwifi.com.br) ele pode liberar ou acessar a Internet quando fornecida.
Usando Computação Aplicada
seria possível extrair frames e o áudio de alguns vídeos, criando slides, para reduzir o tamanho dos arquivos.
Desafios encontrados
Desenvolvimento com poucas pessoas e recursos.
Realizações das quais me orgulho
Troca de conhecimento e educar joves
O que eu aprendi
A cada interação mais experiência e conhecimento se obtém e quando se ensina isto é exponencial.
O que terá de novo neste projeto
Ter tutores e colocar o EAD conectado na Internet para ter correções rápidas para os estudantes.
Ter investidores, organizações e prefeituras para investimento de antenas, o sinal atinge um raio maior reduzindo equipamentos e possível manutenção.
Built With
api
node.js
react
Try it out
github.com
sites.google.com
plataforma-ead.herokuapp.com
docs.google.com
www.loom.com
educacao.uol.com.br | EAD nas Comunidades | Disponibilizar um EAD para a comunidade e alunos da rede de ensino em uma rede Wi-Fi. | ['diana calheiro', 'Bruno Miranda A. Araújo'] | [] | ['api', 'node.js', 'react'] | 59 |
9,914 | https://devpost.com/software/mercado-futuro | Capa
Lean Canvas
Inspiration
As empresas, principalmente as varejistas, que
não são consideradas como essenciais
o seus funcionamentos, tiveram que encerrar suas atividades de forma
repentina
.
What it does
plataforma em que pequenos negócios poderão ter acesso à dinheiro de forma rápida através da
venda de Vouchers
pré-pagos, onde os clientes programam suas compras futuras, ajudam e valorizam o comércio local e ainda ganham bônus.
How I built it
Protótipo Funcional desenvolvido em React.
Challenges I ran into
Fazer toda a prototipação e aplicar modelagem de design UX e UI. A parte de validação também foi difícil, pois todas as entrevistas tiveram que ser online ou via formulários.
Accomplishments that I'm proud of
Enregamos uma solução validada e que irá beneficiar os negócios locais nesse contexto de pandemia e de medidas de isolamento social em que estamos vivendo atualmente, que impactou de forma muito agressiva a economia como um todo..
What I learned
Aprendemos a validar um modelo de negócios através de pesquisas e mentorias.
What's next for Mercado Futuro
Queríamos escalar a solução, oferendo ela de forma gratuita durante essa pandemia. Para isso, estamos na fase de buscar parcerias e apoio de mentores de várias instituições também, como Sebrae, colocar o site no ar, ajustar mais um pouco o layout do site, para melhorar a UX e UI, e fazer toda a parte de backend.
Built With
react
Try it out
bit.ly
github.com
bit.ly
bit.ly
bit.ly | Mercado Futuro | Programe suas compras futuras, ajude e valorize os pequenos negócios e faça seu dinheiro render mais que na Poupança! | ['Daniel Moura R. Araujo', 'Thainá Monteiro', 'Rodrigo Pauletti', 'João Paulo Terrazam'] | [] | ['react'] | 60 |
9,914 | https://devpost.com/software/data-visualization-and-crowd-analysis-using-ml-techniques | Splash screen
User app Home page
User App- Home screen
Website Home page
Admin app - Authentication
Admin app - Set limit
In recent years, the human population is growing in extreme rate and hence the growth has indirectly increased the incidence of the crowd. There is a lot of interest in many scientific research in public service, security, safety and computer vision for the analysis of mobility and behavior of the crowd. Due to a crowded crisis, there are large crowds of confusion, consequence in pushing, mass-panic, stampede or crowd crushes and causing control loss. To prevent these fatalities, automatically detection of critical and unusual situations in the dense crowd is necessary. People visiting various malls and students studying in universities face a lot of difficulty because of the rush. So far there has not been any significant improvement to tackle this problem effectively. Our project aims to tackle this issue by providing a system for collecting, processing and visualizing the crowd behaviour. The end result of our system is a web and app user interface where users can browse through a range of information related to the crowd distribution and crowd movement within a campus and a city.
This project combines the power of Wifi devices, Big data, Machine learning and Data Visualization techniques to promote smart living and management. The main idea of this project is to analyze the CCTV in real time and tracking the Wifi probe requests of users for automatically sensing the crowd distribution and to provide statistical data to the users. The use of big data is to analyze and predict the level of crowdedness among the various places in the city and inside the campus also. It also captures the crowd movement to locate critical and crowding spots effectively. Furthermore, it monitors the crowd conditions and waiting time at important locations such as bus stops, railway stations, airports, religious places, campus canteen and uses Artificial Intelligence techniques to predict the upcoming crowd. For example, people can check the current crowdedness conditions and waiting time at bus stations and make smarter decisions on their mobility. Through big data analysis, people can not only compare the crowdedness but also can avoid the peak hours by AI prediction.
In this Pandemic situation, Social distancing is in much importance, without which there is a high risk of people getting affected by the virus. So we can use the surveillance cameras that are available at many location and compute, analyze the crowd density of a particular location. If the crowd density of a particular location is found to be greater than the allowed crowd density, we can alert the police authorities and it would be a great use for them to track the people who are not following the rules that are put forward by the government ie, we can prevent large crowd gathering which may lead to more people getting affected.
Crowd detection and density estimation from crowded images have a wide range of application such as crime detection, congestion, data driven smart campus, public safety, crowd abnormalities, visual surveillance, urban planning, bus stations, restaurants and various other places. Nowadays, crowd analysis is the most active-oriented research and trendy topic in computer vision. As a result, it will definitely help to make emergency controls and appropriate decisions for security and safety. This system can be used for the detection and counting people, crowd level and also alarms in the presence of dense crowd.
The objectives of this project are: Develop an automated system for collecting and processing input data. Develop algorithms for observing the crowd size in various places and predicting the crowd. Raise alarms in the case of over crowdedness. Design and build database for data storage. Build an intrusive app and web user interface for visualizing the crowd distribution and crowd movement information.
Thus, our project handles the difficult issue of including the quantity of items in pictures, a universal, principal issue in computer vision. While people and computer vision calculations, are profoundly blunder inclined, our algorithms and IOT devices consolidate the best of their abilities to convey high accuracy results at moderately low expenses providing an effective solution for this imminent problem.All these are back-end working of a web interface and a app that allow authorized person to sign in and gather the details about the targeted location from anywhere.
Built With
android
css
firebase
html
java
javascript
python
regression
sdc-net
spyder3
website
xml
Try it out
he-s3.s3.amazonaws.com
github.com
drive.google.com | Data Visualization and Crowd Analysis using ML Techniques | Real time crowd analysis in crowded places by using AI in CCTV footages | ['Rithik Jain', 'Vimal Kumar', 'Godi SaiTeja', 'Vijay Krishnaa'] | [] | ['android', 'css', 'firebase', 'html', 'java', 'javascript', 'python', 'regression', 'sdc-net', 'spyder3', 'website', 'xml'] | 61 |
9,914 | https://devpost.com/software/challengehomecovid |
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Olá a todos. Me chamo Ingrid Assis e sou uma das criadoras do desafio "ChallengeHomeCovid" juntamente com Ana Alicia Medina e Karen Nascimento.
Somos estudantes da rede pública e estamos no terceiro ano do ensino médio. Nosso colégio é vinculado com o INMETRO, então, além de estudantes do ensino médio somos estudantes dos cursos técnicos de metrologia e biotecnologia.
A nossa ideia tem como objetivo auxiliar pessoas que passam por problemas psicológicos, como a ansiedade e depressão, além de proporcionar uma interação entre as pessoas e promover um divertimento a todos nesse período. Um estudo da Universidade do Estado do Rio de Janeiro mostrou o crescimento do número de casos de depressão em quase 50% e de ansiedade em 80% desde o início da quarentena no Brasil. A pesquisa mostrou que as mulheres são mais propensas a sofrer com estresse e ansiedade durante o isolamento social, em especial as que precisam sair de casa para trabalhar, as que têm doenças preexistentes e são sedentárias.
Nossa ideia é criar um aplicativo com diversos desafios que serão realizados dentro da própria casa. Ao criar o aplicativo, uma conta é criada e essa pessoa/família pode criar uma sala ou aceitar o convite de alguém para participar de uma e assim começam os desafios.... Nesse aplicativo terá desafios físicos, quiz de perguntas e respostas. E os participantes poderão competir entre si ou com pessoas de outras residências. A cada partida vencida o participante ou a família recebem pontos. Esses pontos vão acumulando e liberando novas salas e com novos desafios. Esses desafios serão divididos de acordo com a faixa etária do usuário, para poder atender a todos os usuários.
Precisamos de ajuda para colocarmos essa ideia em prática. Precisamos de pessoas que entendam de design, programação, entre outros. Inspiration | CHALLENGEHOMECOVID | CHALLENGEHOMECOVID venha se divertir com a gente. Cada um na sua casa. | ['Ingrid Assis', 'anaaliciamsrn'] | [] | [] | 62 |
9,914 | https://devpost.com/software/vera-true-news | Banner do projeto
Inspiração
A proliferação desenfreada de notícias falsas e os problemas sociais que ela acarreta, em especial em relação à saúde pública dado o cenário atual, inspiraram uma série de iniciativas. Entre elas estão o
link
[Health Buddy], um chatbot desenvolvido pela Unicef que responde dúvidas comuns e aceita denúncias de notícias falsas, o canal de mensagens Saúde sem Fake News desenvolvido pelo Ministério da Saúde e o aplicativo Eu Fiscalizo, da Fiocruz, que aceita denúncias de notícias falsas.
O que faz
Vera Verificadora é um chatbot que pode ser contatado via mensagens de Whatsapp para verificar se uma determinada notícia é verdadeira ou falsa. O texto enviado para o bot é analisado por meio de um modelo de Machine Learning que analisa fatores como fonte, frequência de palavras e outras variáveis para avaliar se a notícia é verdadeira ou falsa. Acreditamos que a análise automatizada das notícias representa uma grande vantagem pois possibilita ao usuário uma interação mais instantânea.
Ao mesmo tempo, ao criarmos uma personagem para interagir com o usuário, é possível pessoalizar a interação e criar uma marca reconhecível, além da personagem falar em português e utilizar uma linguagem acessível para que todos possam ter acesso a verdade. Esses aspectos tornam nosso projeto mais efetivo na disseminação de informação verdadeira.
Como construímos
Utilizamos como base o trabalho Towards automatically filtering fake news in Portuguese, por Renato M. Silva, Roney L. S. Santos, Tiago A. Almeida, Thiago A. S. Pardo
link
para treinar um modelo de Machine Learning, com dados do fake.br Corpus
link
. Criamos então um chatbot com a plataforma Twilio para possibilitar que o usuário rode o algoritmo de Machine Learning via interação com o bot.
Desafios
O principal desafio foi o curto tempo para o desenvolvimento de uma ideia que visa lidar com uma situação tão complexa quanto o alastramento de notícias falsas. A presença de estudos e dados de treino que permitiam a implementação do modelo de Machine Learning foi fundamental para que o protótipo pudesse se tornar realidade.
Feitos de que nos orgulhamos
Apesar das dificuldade de tempo, conseguimos construir um protótipo funcional para a Vera e apresentá-lo para avaliação. Também criamos uma maravilhosa e simpática identidade visual para a nossa robô.
O que aprendemos
Aprendemos que existem muitos fatores que devem ser considerados ao se analisar se uma notícia é falsa ou verdadeira, de forma que a automatização desse processo não é uma tarefa fácil e requer constante estudo e aprimoramento para termos bons resultados.
Próximos passos para a Vera Verificadora
Alguns dos próximos passos para a Vera incluem:
Aumentar a base de dados de notíciais verdadeiras e falsas usadas pelo nosso modelo e planejar sua atualização constante, de preferência, colaborando com outras iniciativas que realizam a apuração de notícias falsas, como o aplicativo Eu Fiscalizo.
Implementar uma funcionalidade que permitirá à Vera não apenas responder ao usuário com links de notícias verdadeiras, mas transferir estas informações para dentro do chat.
Implementar funcionalidade que permite que Vera analise notícias não apenas com base em links, mas em textos soltos e imagens.
Aumentar nossa equipe e planejarmos uma campanha para divulgação e incentivo do uso da Vera
Trabalhar junto de outras iniciativas para investigar as fontes das notícias falsas e entender o seu mecanismo de propagação.
Built With
api
node.js
r
twilio
Try it out
github.com | Vera Verificadora | Um chatbot que recebe mensagens com links para notícias e responde dizendo se a notícia é (provavelmente) falsa ou verdadeira e fornece links para notícias similares confiáveis. | ['Clara Garcia', 'Jacson Feiten', "Nina O'Neill", 'Lucas Limberte'] | [] | ['api', 'node.js', 'r', 'twilio'] | 63 |
9,914 | https://devpost.com/software/saude-2-0 | Inspiration
D045 - CONECTANDO PACIENTES, MÉDICOS E FARMÁCIAS EM MOMENTOS DE ISOLAMENTO
D046 - REDE COLABORATIVA DE AJUDA E APOIO NA SAÚDE
D047 - SUPORTE A ENFERMAGEM
D070 - SISTEMA PARA REGISTRO DO HISTÓRICO DE SAÚDE DE PACIENTES
D124 - SAÚDE TRANSPARENTE PARA TODOS
D149 - SAÚDE, PRIVACIDADE E BLUETOOTH: COMO ENGLOBAR OS TRÊS CONCEITOS EM UM APP
.
What it does
Coletar dados médico-hospitalares relativos a um paciente de maneira segura, abrangente e rápida.
Garantir o lastro da informação por meio da autenticidade dos proponentes (médicos, enfermeiros, laboratórios) e do consentimento do próprio paciente.
Garantir ao paciente a posse de seus dados, em atendimento à LGPD, e permitir que os médicos tenham acesso a todos estes dados, dado o consentimento do paciente, independente do local em que o paciente é atendido.
Facilitar o acesso e compartilhamento de dados médicos.
.
How I built it
Embora muitos países já estejam adotando a tecnologia blockchain de maneira progressiva, especialmente da digitalização de prontuários e outros dados da saúde, no Brasil ainda existem milhares de unidades de saúde, clínicas e hospitais que sequer adotaram a informatização dos seus dados. Recentemente a Alemanha contratou uma empresa especializada em Blockchain para rastrear os exames de diagnóstico de COVID19.
Por aqui, temos novos e velhos problemas que impedem de sonhar tão alto. Apenas como um exemplo, no primeiro trimestre de 2020, um incomum período de chuvas afetou diversos municípios de Minas Gerais, causando cheias inéditas. Estas enchentes atingiram unidades de saúde, clínicas e vários órgãos públicos municipais, como na cidade de Ubá onde vários dados de cadastro de usuários de bolsa de colostomia e vítimas de tuberculose se perderam, pois não possuía nenhum sistema onde estes dados fossem arquivados de maneira permanente.
Em uma pesquisa prévia, detectamos diferentes graus de qualidade dos sistemas de saúde do mercado, sendo que muitos hospitais ainda adotam sistemas antigos, que rodam no sistema operacional DOS. Outros, um pouco mais evoluídos utilizam bancos de dados em um servidor central, com estações comunicando via protocolo TCP IP.
De fato muito ainda precisa ser feito para se alcançar um grau de qualidade melhor dos sistemas digitais na área de saúde, seja na esfera dos governos ou até nas redes privadas de clínicas, planos de saúde e hospitais. Tão logo estes sistemas sejam ajustados, provavelmente já enfrentam novos paradigmas, como a nova Lei Geral de Proteção de Dados, o avanço da Telemedicina, e o surgimento de aparelhos médico-hospitalares mais modernos que precisam ser integrados ao sistema.
Nossa plataforma Saúde 2.0 propõe uma série de inovações na abordagem deste problema e desafia os sistemas de informação tradicionais de saúde, apontando suas limitações e discutindo novas alternativas que possam ser efetivamente implementadas.
.
Challenges I ran into
Não encontramos desenvolvedores para o projeto dentro do hackaton.
.
Accomplishments that I'm proud of
Criamos uma solução que irá revolucionar a informação de saúde dos pacientes, e estamos realmente ajudando a construir um mundo melhor.
.
What I learned
Aprendemos mais informações sobre blockchain.
Aprendemos a contribuir com um repositório Github
Aprendemos como criar um SCHEMA na plataforma EUGENIO.
.
What's next for Saúde 2.0
Implementar um protótipo de um dispositivo EUGÊNIO integrado na Blockchain
Implementar o dashboard com dados dinâmicos
Implementar um chatbot para conversar com os pacientes
Implantar em um laboratório (Case)
Implantar em uma clínica (Case)
Implantar em um hospital (Case)
Implantar em um governo municipal (Case)
Implantar em um governo de maior abrangência
.
Built With
blockchain
node.js
python
react
Try it out
sislivre.com.br
github.com
xd.adobe.com
docs.google.com | Saúde 2.0 | Saúde 2.0 é uma plataforma de coleta de dados médico-hospitalares referentes a prontuários médicos, consultas, diagnósticos, exames laboratoriais e todo tipo de informação da relação médico-paciente. | ['Rogério Santos', 'Ricardo da Rocha Vitor', 'Amanda Barbosa', 'Daniela Ribeiro'] | [] | ['blockchain', 'node.js', 'python', 'react'] | 64 |
9,914 | https://devpost.com/software/covid-xn8iow | Inspiration
In November 2018, we competed in the Congressional App Challenge in U.S. Representative Eddie Bernice Johnson’s congressional district. Since we had numerous relatives who have Alzheimer’s Disease or other forms of dementia, we were inspired to combine our passions in community service and technology to design an app for Alzheimer’s patients. Following two years of refinement and development, we won our district’s Congressional App Challenge. The U.S. House of Representatives invited us to go to Washington, DC, to present this app to the U.S. House of Representatives (
link
.)
The rising impact of the COVID-19 outbreak on a community, regional, national, and international level inspired us to use our mobile app development experiences to find a solution that addresses major areas of the problem. As children, we realized that isolation and social distancing could lead to stressful situations for numerous individuals, particularly children. As a result of this, we learned that children who live in an abusive situation are at more substantial risk. This risk is especially significant due to the isolation that COVID-19 mandates. We realized that community members need to have a greater awareness of the signs and symptoms of child abuse and neglect during this stressful time and the numerous resources available to the children who fall victim to subsequent maltreatment. This risk, experts have shown, could result from isolation, lack of answers, lack of structure to the day, and the lack of things to look forward to - all effects of COVID-19.
As students, we believe we can impact society, big or small, with our idea. Technology is indeed the future, and we need to make sure that we adopt the tools that we use to help, entertain, to assist child abuse victims in being very reflective of these advances. Furthermore, we hope to use our application to inspire and encourage other involved students in our district and even around the state to get involved in coding and also develop their apps for problems that are personal to them. If we were to win the competition, we plan to continue to use our platform to help further encourage and inspire others and show other legislators the importance of the problem we are trying to address.
What it does
Our application, Coaware (COVID + Aware), contains a questionnaire/checklist consisting of eight questions designed in collaboration with child abuse prevention experts such as the Baltimore Children's Advocacy Center.
The checklist contains a different method for users to organize their thoughts but contains the same question format. Next, the app provides an option to provide the user with child abuse prevention hotlines or children's advocacy centers. If the user toggles this option, the app will provide these resources based on their location.
However, according to many experts, Coaware's most important feature is its generation of
email logs
. These logs provide users with a method to organize their thoughts, allowing them to access a particular child's responses from weeks or even months. When the user reports child abuse, they can detail previous dates alongside specific symptoms of child abuse the child was exhibiting at the time.
How we built it
We built our application using Java and XML in Android Studio. We used a relative layout format with tab-based fragments for the first tab and a corresponding layout design with intent fillers for the second tab’s functionality. For the user interface, we utilized AAA contrast for the vast majority of the app to enhance usability and readability for all users.
Challenges we ran into
Our first significant difficulty was to make the application and user-interface simple enough to be operated by any individual. We had to navigate and test out various fonts, image sizes, color combinations, and table setups to make sure that the app was clean and simple to operate without compromising the usefulness of its features.
The second technical challenge we faced in creating the application was making sure that it would be functional across various Android Platforms. The problems that we ran into would vary from device to device, so it was challenging to come up with a solution that worked for every single one and didn’t create problems of its own. We ran several tests on a variety of Android emulators and tested the application on a wide array of personal devices and were eventually able to come up with a solution that worked across the boards. This process was eye-opening for us, as we never realized how seemingly small changes could have drastic impacts on different devices.
The final challenge we are currently dealing with is getting Coaware into the hands of the people who need it the most. We are currently in discussions with schools and children's advocacy centers to accomplish this task.
Accomplishments that we’re proud of
Some accomplishments that we’re proud of deal with our app for Alzheimer’s patients, AlzBuddy, which inspired us to make this app. The U.S. House of Representatives invited us to showcase AlzBuddy to them in the U.S. Capitol Building. Individually, numerous State and National Congresspeople have invited us to demonstrate our application. Fox 4 News also interviewed us (
link
). AlzBuddy was also named the 1st Runner-Up in the national Diamond Challenge at the Sam Houston State University Pitch Location. We are also proud to have many downloads after approval of our application onto the Google Play Store. We want to use our experience and success to continue to propel Coaware to help children globally. Additionally, our group was named Conrad Innovators by the Conrad Foundation for both AlzBuddy and Coaware.
What’s next for Coaware App
Overall we are delighted with our final product, and we were able to make a lot of improvements from the last app we created to this one. That said, we would always love to be able to improve the app even more, and we know that there are improvements to be made, we just didn’t have the time to make all of them. We know that we can always improve, incorporate more valuable feedback, and learn from our mistakes. One challenge that we would have to face if we decided to develop the app, however, would be maintaining a clean, simple interface despite having more functions. In this specific field, we have to understand that less is sometimes more. Potential technological additions will include modules and relaxing games for child abuse victims, networks for victims to share their stories in a peer-network, as well as possible chatting services within the app in partnership with abuse hotlines.
We are currently in the process of publishing our application in the Google Play Store as well as developing an iOS version of our app. In addition to this, we are working on collaborating with various non-profit organizations that specialize in child abuse awareness at a community and regional level. We have objectively networked with various legislators to start district initiatives and launches of our application.
Success in this global hackathon will help us launch Coaware worldwide to protect the thousands of children that fall victim to child abuse.
We are also looking to expand our app to other areas, such as domestic violence, whose rates, unfortunately, skyrocketed during the coronavirus pandemic.
Built With
android-studio
java
xml
Try it out
play.google.com | Coaware | Our application, Coaware (COVID19 + Aware), has functionalities designed for emergency situations regarding child abuse prevention, a rising social issue due to increased isolation from COVID-19. | ['A B', 'Vedant Tapiavala'] | [] | ['android-studio', 'java', 'xml'] | 65 |
9,914 | https://devpost.com/software/i-vent-ventilacao-pulmonar-de-baixo-custo | Protótipo ventilador pulmonar
Mesa de trabalho durante o hackCOVID19
Testes durante a prototipação do ventilador pulmonar
Montagem do dispositivo
Protótipo em funcionamento de teste
Modelo 3D do iVent versão final
Modelo 3D do iVent, versão inicial
Processo Criativo, ferramentas de Trabalho
O QUE INSPIROU
A insuficiência respiratória é uma das principais causas de morte por COVID19 de acordo com a Organização Mundial da Saúde. Quando o vírus chega e se alastra nos pulmões, causa uma pneumonia. Na ânsia para se livrar do agente infeccioso, o corpo reage produzindo mais fluidos e substâncias inflamatórias, que ocupa os alvéolos, as pequenas estruturas onde ocorrem as trocas gasosas e que permitem disponibilizar o oxigênio ao organismo. Mesmo nas grandes cidades, há escassez de ventiladores pulmonares.
Saulo Dansa, o responsável principal pelo projeto, acompanhou de perto como observador o avanço dos projetos de prototipação de ventilador pulmonar da USP, UFRJ e do MIT. Observou-se que poderíamos desenvolver um ventilador pulmonar com peças totalmente compradas no Brasil, sem uso de impressão 3D nas peças principais, assim como poderia reduzir o custo de desenvolvimento, algo que se apresentou ser um grande desafio para estes institutos e universidades.
A equipe do projeto acredita que, por ser um respirador alternativo, poderíamos impactar o atendimento de pacientes em hospitais de cidades menores onde não há tanta disponibilidade de respiradores convencionais utilizados em terapia intensiva e os pacientes precisem ser transferidos para hospitais nos grandes centros que já se encontram no limite da capacidade.
O QUE APRENDEU
Parceria é tudo! Conseguimos em parceria com instituições e contatos com outros pesquisadores, solução para muitos problemas técnicos enfrentados. Pessoas da COPPE, IFRJ, UERJ, entre outras estão conosco construindo esta solução. Ao longo da trajetória desse desafio, inicialmente listou as peças principais necessárias pra realizar a construção do aparelho. Se deparou com a necessidade de uma equipe multidisciplinar, para verificar os requisitos mínimos solicitados por agências de regulação como a ANVISA, assim como a importância do aprimoramento do algoritmo. Para além dessas situações, a equipe técnica aprendeu a importância que alarmes de segurança entre outros dispositivos fossem acionados para evitar que o aparelho ficasse inativo, já que vidas dependem do seu bom funcionamento.
COMO CONSTRUIU
O iVent é um ventilador pulmonar baseado no modelo proposto pelo MIT, construímos uma solução funcional implementando controles para os parâmetros de Volume Corrente, Frequência Respiratória e Relação entre os tempos de IE (Inspiração e Expiração). Depois de listar as peças necessárias, criar o modelo 3D de como serial idealmente o ventilador, elaborar um diagrama elétrico da solução, entre outras etapas de planejamento, foi criado o protótipo que apresentamos neste hackathon!
O tempo total dos inputs define a frequência respiratória (respirações por minuto). Utilizando arduíno, entre outras tecnologias conseguimos fazer com que um braço mecânico (impulsionado por um motor) gere uma compressão contra um AMBU (bolsa de ressuscitação manual), para gerar um fluxo respiratório ao paciente. Conseguimos implementar um filtro bacteriológico entre a traqueia de expiração (uma extremidade do ambu, mangueira que leva volume ofertado até uma peça que se conecta ao paciente por meio de uma máscara oronasal, ou por um tibo orotraqueal, inflando os pulmões). Além do filtro umidificador, entre a peça e o paciente, que umidifica, filtra e aquece o ar. Durante o hackathon, inserimos outras funcionalidades, melhoramos nosso protótipo e estimamos outros desafios a serem enfrentados para seguirmos com a regulamentação do nosso dispositivo.
Foi construído com recursos próprios, sem fonte de financiamento, de maneira colaborativa com outros especialistas, técnicos, programadores, engenheiros, designers e profissionais da saúde. Maior especificação do projeto, consta no vídeo Pitch. As imagens do nosso processo, está acoplada aqui nos anexos.
DESAFIOS QUE ENFRENTOU
Um dos principais desafios foi durante a pandemia ir comprar as peças que eram necessárias de última hora. Mas a partir de parcerias com outros coletivos hackers no Rio, conseguimos um motoboy para auxiliar nesse processo. Também tivemos dificuldades em contactar fornecedores diretos, e a maioria das nossas peças foram compradas em lojas de ferragens, materiais de construção e no Mercado Livre, mas gastamos apenas cerca de R$313,26, sendo esse um dos nossos principais diferenciais. Tal situação mexe com o valor total do orçamento, por isso estimamos o valor total do protótipo entre R$350,00 e R$500,00.
Mesmo com muita pesquisa de profissionais da área técnica sobre as normas de regulação da ANVISA, mesmo ao final do hackathon ainda temos muitas dificuldades, sendo um fator de desânimo pros desenvolvedores pois parece inalcançável apenas com os recursos que dispomos. Precisamos muito de mentoria nessa parte.
PLANOS FUTUROS
Entramos nesse Hackathon com o objetivo de conseguir apoio para aprovação do equipamento junto à Anvisa, através de parceiros, mentoria e conexões com instituições como o NIT podem nos ajudar com isso.
Num segundo momento, vamos precisar também de fabricantes interessados em produzir esse equipamento numa escala maior para atender à necessidade dos hospitais.
Contato:
ivent.colab@gmail.com
Built With
arduino
c++
github
googlemeet
impressora3d
rhinoceros3d
slack
trello
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github.com | I.vent: ventilação pulmonar de baixo custo. | I.vent: um respirador alternativo de produção barata, rápida e fácil para ajuda em situação de emergência epidêmica. | ['Anny Caroline Sousa', 'Diego Savelli', 'Yuri Lima', 'Clara Dansa', 'jasmin dansa', 'Manuchi Dansa', 'Matheus Nunes', 'Pedro Henrique de Albuquerque', 'Saulo Dansa', 'Stella Savelli', 'Paulo Paz', 'Jose Júnior', 'Luigi Ribeiro'] | [] | ['arduino', 'c++', 'github', 'googlemeet', 'impressora3d', 'rhinoceros3d', 'slack', 'trello'] | 66 |
9,914 | https://devpost.com/software/evolution-fi16oj | Greetings from Greece.
A Global center “World Health Bank” must be set up for the collection of the biological material of all the patients of the world who suffering from diseases with the right hierarchy of secret e-data (after an agreement), with new safe & secret telecommunication system (quantum telecommunications or something more sophisticated & secret), with new safe & secret internet (quantum internet or something more sophisticated & secret which will use blockchain, ghost polarization communication, quantum cryptography, chaos cryptography or newer sophisticated secret cryptography technology or a combination of all together), with global cloud computing, with DNA digital data storage, with machine intelligence, with artificial intelligence, with computational intelligence, with evolutionary computation, with machine learning, with deep learning, with machine vision, with automation & with the best scientists on these fields.
Biological material to be diffuse into full body – organism connected microchip – robotic organs [human organs-on-chips or human organism-on-chips or human body-on-chips or human-on-chips (from cells, stem cells & etc of the patients – people)] or into full body – organism connected printed organs (from cells, stem cells & etc of the patients – people) by multidimensional biological printers for personalized testing & continuous monitoring of patient’s biological -genetic (substances) reactions in vitro, to record the disease before tests & the cure (on molecular – submolecular – atomic – subatomic – etc levels) after continuous monitoring of multiple tests in multiple full body – organism connected microchip organs & in multiple full body – organism connected printed organs for each person – organism individually in order to understand in maximum levels everything about the confrontation of diseases.
Evolution of all type of genetic – biological material [injection of modified – evolved all the type of cells like evolved NK cells (injection into Thymus), like evolved B-cells (injection into Bone Marrow), like evolved killer & helper T-cells (injection into Thymus & Bone Marrow) & like etc at the right organs with evolved their DNA-RNA bases via Prime Editing, Cas-CLOVER, ABE8e, ABE8s, CRISPR-CasRx, irCLASH, CRISPR-Cas13 system & generally via all CRISPR-Cas systems & FluidFM together with evolved their double stranded DNA helix & etc] will lead us to the armour of our organisms from every disease & virus & maybe will lead us to immortality up to a point.
There will be the technology to replace the real tissues – organs – neurons – etc by bioprinted tissues – organs – neurons – etc or by robotic tissues – organs but it is better to achieve the regeneration of the tissues – organs by changes to the blood that contains our DNA – RNA – etc. Scientists should focus on the manipulation of blood substances for regenerative medicine in order to do not need the people transplantations of simple or biological or robotic tissues, organs, neurons & etc.
If DNA – RNA have A – B & C – D letters – bases to the edges, scientists can add – insert – embed – consolidate there in the same edges (with Base Editors or with something more sophisticated) respectively [A – etc (A-Z) or B – etc (A-Z) & C – etc (A-Z) or D – etc (A-Z), for example A – B – A – C – A – D – etc or B – A – B – C – B – D – etc & C – D – C – E – C – F – etc or D – C – D – X – D – Z – etc] letters – bases with the other edges of them to be new letters – bases for evolution or to add – insert – embed – consolidate a Synthetic DNA with the letters – bases from another organism or organisms to the existing DNA – RNA (after safe clinical trials) & later to evolve the polynucleotide chains [[DNA Strands – DNA double stranded helix (via Rad proteins with their helper proteins generally & via Rad51 with its helper proteins [called Swi5Sfr1 (with evolved yeast cells) & Rad51 paralogs] to awake HR pathway in the repair of DNA double-strand breaks especially, via protein DNA-PK, via protein TEX264 with its enzymes & etc]] that are the guards of our kind’s genetic code together with p53.
Scientists will be ready to add more evolved artificial strands (if it is safe) to the already double stranded DNA helix (which it will be evolved) if they find the right combinations of evolved artificial bases with the already existing bases (which they will be evolved).
Scientists can also edit – modify – evolve all the other genetic – biological material like DNA (with its subcategories), RNA (with its subcategories), genomes, epigenomes, genes, chromosomes, chromatins, polynucleotide chains, CAS systems, microglia, cortices, microbiomes, neurons (neurotransmitters – neuropeptides – etc), cell membranes, cells [injection into Bone Marrow of evolved immunoglobulins (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) & injection into Thymus & Bone Marrow of evolved killer & helper T-cells (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) with receptors that recognize the molecule which called MR1, with receptors that recognize the molecules of cancerous EVs & generally all the specific molecules of cancerous & viral cells in order to destroy them & to propagate & evolve all the other simple T-cells that exist into Thymus & Bone Marrow & it can also become injections of EBC-46 directly to the cancer – tumors in order to kill them in a record time after successful experiments with safety to the humans & injection of all the other type of edited cells on their specific tissues], stem cells, telomerase, telomeres, proteins, lipids, amino acids, acids, enzymes, microbes, mitochondria, exosomes, molecules, molecules, submolecules, atoms, subatomic particles & everything other that exist with their subcategories.
Evolution of all the antibodies & all the receptors of all the evolved cells like NK-cells (injection into Thymus with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost), like B-cells (injection into Bone Marrow with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) & like T-cells (injection into Thymus with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) & etc in order to recognize all the specific antigens & generally all the specific molecules – submolecules of cancerous & viral cells in order to destroy them. Also, evolution of immunoglobulin therapy [evolved immunoglobulins (to recognize all the dangerous antigens)] & evolution of synthetic TRuC receptors (to recognize all the dangerous antigens) which will evolve old ones through injections for the confrontation of diseases & viruses.
Transformation of fat & cancer – viral cells (when it will be safe) into healthy pluripotent stem cells [with the ability of modification to any type of cells (with evolved genetic – biological material)] which will have an ability to change through controlled transmission the genetic – biological material of old cells will extend life. Together with the reprogramming of old cells into youthful state with evolved double stranded DNA helix, DNA (with its subcategories), RNA (with its subcategories) & generally with evolved all their genetic – biological material with its subcategories will transform us into immortals up to a point.
As the cancerous & viral cells interact, infect & transform through transmission the healthy cells, scientists must find the way to use the same action with evolved cells (with evolved their genetic – biological material with its subcategories) in order to evolve the organisms as we want. Maybe the technique called genetically targeted chemical assembly, or GTCA can help scientists to do it.
If scientists reprogram old cells into youthful & evolved cells & if they reprogram cancerous & viral cells into evolved healthy ones or into healthy iPS cells (when it will be safe) with selected, automated & controlled replication & replacement through the consign of a correct signal on all the organism via a vaccine which will contain biodegradable mimetic scaffolds (in order to give them a boost), they will extend organisms life duration. Another way to eliminate cancer & viral cells from organisms is to trigger selective apoptosis to them after the identification of their specific cancerous & viral molecules – submolecules.
Scientists must reach the level where they will insert nanites which will identify all the cancer & viral cells of organisms in order to trigger selective apoptosis to them or differentiation to them into healthy cells after the identification of their specific cancerous & viral molecules – submolecules.
If scientists could transform all the cancer & viral cells into ES cells & iPS cells which will contain GATA3 gene & which will contain commands in order to become any type of cell we want, they would pass to the next level of treatment.
The cure of every disease is easy from the time that scientists will discover all the bad antigens – molecules – submolecules in order to evolve all the receptors & antibodies for a targeted attack to them via personalized targeted biodegradable nanites or via biomolecular reactions.
It should become also mass bombardment every 3 – 6 months on the organisms with biological – light – sound – wave – vibration – pulse – magnetic – electrical – etc stimulations & with FLASH radiotherapy (when it will be safe) on all the body at the same time in order to wake up the functions of the organisms.
Scientists should create biological printed (bioprinted) tissues – organs – neurons – etc & robotic tissues – organs – neurons – etc which will charge – load from the body pulses & which will charge – load from the wireless networks such as the RFID microchips – biosensors implants respectively in order to replace the real ones which have problems or to find ways for the regeneration – evolution of our tissues, organs, neurons, cell membranes, cells, stem cells, telomeres, proteins, lipids, amino acids, acids, enzymes, microbes, mitochondria, exosomes, molecules, submolecules, atoms, subatomic particles & etc with their subcategories, ways for the armor & evolution of DNA, RNA, polynucleotide chains (double stranded DNA helix), genomes, epigenomes, genes, chromosomes, chromatins, CAS systems & etc with their subcategories. Finally, ways for the clearance – evolution of our veins throw safe personalized medicines or safe personalized vaccines which will contain molecular machines – nanites for the extension of life duration.
The creation also of nanoscale RFID biosensors – microchips (nanites) that will be implanted inside our organisms after an agreement via vaccines in order to analyze – monitor in real time all the biological data – material – substances of the organisms for the prevention of all the type of diseases (tumors – cancer, aids & etc) with the combination of multidimensional printed biological or microchip organs inside from multidimensional biological – biochemical printers for experiments in vitro (outside of the patient’s body) with our DNA, RNA, cells, stem cells & etc will lead us to the disappearance of diseases due to the early diagnosis, due to extra fast experiments & due to personalized polypills [it will contains nanoscale microscopic RFID microchips – biosensors which called nanites (creation of body – organism gps) in order to release the right substances at the right place] – vaccines that will also be printed by multidimensional biological – biochemical printers that will exist in every hospital – health center of the planet.
For more analysis, scientists could insert after an agreement to all the organisms implantable nanites which will be RFID microchips – biosensors (Hitachi’s Smart Dust or more sophisticated nanites) & which they will hook – connect to the cardiovascular system & especially on the valves of heart with automation or with commands from them in order to analyze all the time all the genetic – biological material for the prevention from diseases – viruses through nutrition or through personalized medicines – vaccines from multidimensional biochemical printers. They must reach the level where could implant through vaccines at heart valves different stable (deep-rooted – ingrained at heart valves in order to stay there forever) nanofibrous mimetic scaffolds with deep-rooted – ingrained evolved all the genetic – biological material & with deep-rooted – ingrained nanites which will be biosensors in order to evolve & analyze all the genetic – biological material of the cells through the flow of cardiovascular system. Scientists could insert also after an agreement implantable nanites through vaccines which will be RFID microchips – biosensors & which they will hook – connect to all the organs, neurons & etc of the organisms with automation or with commands from them in order to check all the time the vital functions & the vital situations of the tissues, organs, neurons & etc.
The RFID microchips – biosensors will charge – load via the wireless network & via organism’s pulses & they will be from biodegradable materials in order to be dissolved after years (with automation or with commands from the scientists) or they will be from durable materials in order to stay there connected forever. The implantable RFID microchips – biosensors will be quantum stealth nanites without metals but from biological material which will travel through veins (via blood circulation) to the desirable targets where they will hook – connect with automation or with commands from the scientists.
Scientists should use also wireless – quantum – etc networks which exist already & they can monitor the signals of the organisms such as their location, their heart pulses, their breathing rates & etc. They should upgrade them more in order to they can monitor all the rest of vital functions of the organisms & in order to they can decode the brain electrical signals exactly as it happens with electrodes.
The technology that is needed for everything already exists. The matter is to share the scientific data to a specific template – program on the global cloud database through cooperation & coordination all the European hospitals, clinics, health centers, educational institutes, pharmaceutical companies & laboratories. There will be real time monitoring (through the cloud database) of the interactions of the biological material of the patients – volunteers with genetics, biochemistry, nanites & all type of stimulations in order to become the evolution of organisms – life a reality.
The chain of science: Geniuses – top scientists with hazmat suits at BSL-4 laboratories -> very ill animals (that need treatment urgently) & materials -> monitoring & diagnosis [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G-rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with full tests & etc)] -> multiple experiments with the organisms – materials, experiments with FLASH Radiotherapy, experiments with all type of biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations, experiments with all the substances (of periodic table) individually & experiments with all the substances (of periodic table) in a combination until the end of all the combinations -> creations -> continuously monitoring & diagnosis of creations [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with full tests & etc)] -> multiple experiments with the creations (organisms – materials), experiments with FLASH Radiotherapy, experiments with all type of biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations, experiments with all the substances (of periodic table) individually & experiments with all the substances (of periodic table) in a combination until the end of all the combinations -> new creations -> continuously monitoring & diagnosis of new creations [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G-rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with full tests & etc)] -> multiple experiments with the new creations (organisms – materials), experiments with FLASH Radiotherapy, experiments with all type of biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations, experiments with all the substances (of periodic table) individually & experiments with all the substances (of periodic table) in a combination until the end of all the combinations -> newer creations -> continuously monitoring & diagnosis of newer creations [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G-rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with full tests & etc)] -> multiple experiments with the newer creations (organisms – materials), experiments with FLASH Radiotherapy, experiments with all type of biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations, experiments with all the substances (of periodic table) individually & experiments with all the substances (of periodic table) in a combination until the end of all the combinations -> to be continued the chain of science.
Diseases – viruses – microbes – parasites – pathogens treatment: Geniuses – top scientists with hazmat suits at BSL-4 laboratories – > injection on mass scale with the same disease – diseases, virus – viruses, microbe – microbes, parasite – parasites & pathogen – pathogens (experiments with each one disease – virus – microbe – parasite – pathogen each time until the completion of all the diseases – viruses – microbes – parasites – pathogens) on multiple very ill humanized mices & on multiple very ill orangutans – monkeys – apes – chimpanzees – gorillas (generally to all the organisms that have common biological – genetic material with humans) that need treatment urgently in quarantine, on multiple full body – organism connected microchip – robotic organs [full body – organism connected human organs-on-chips or human organism-on-chips or human body-on-chips or human-on-chips (from the cells – stem cells – etc of humans)] in quarantine & on multiple multidimensional full body – organism connected biological printed organs (from the cells – stem cells – etc of humans) in quarantine -> continuously monitoring & diagnosis of the multiple organisms, of the multiple full body – organism connected microchip – robotic organs & of the multiple multidimensional full body – organism connected biological printed organs [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G-rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with mass cytometry, with full tests (blood – excrement – urine – saliva tests & etc) & etc] -> experiments with FLASH Radiotherapy, experiments with electrodes & experiments with all type of biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations at the same time on all the organisms as & on multiple full body – organism connected microchip – robotic organs-on-chips & on multiple multidimensional full body – organism connected biological printed organs, also experiments of individually – separately injections of all the existing medicines – vaccines, of individually – separately injections of all the chemistry periodic table substances, of individually – separately injections of all the simple & edited – evolved biological & genetic material & of individually – separately injections of all the simple & edited – evolved microorganisms & later injections of all the combinations of the medicines – vaccines, of all the combinations of chemistry periodic table substances, of all the combinations of all the simple & edited – evolved biological & genetic material, of all the combinations of all the simple & edited – evolved microorganisms & of all the combinations of all of them (medicines – vaccines, chemistry periodic table, biological & genetic material & microorganisms) together (mixtures) in quarantine on multiple animals, on multiple full body – organism connected microchip – robotic organs & on multiple multidimensional full body – organism connected biological printed organs – > results (from a full test that will show us all the data that can exist about the organisms, about the multiple full body – organism connected microchip – robotic organs & about the multiple multidimensional full body – organism connected biological printed organs) -> continuously monitoring & diagnosis of the multiple organisms, of the multiple full body – organism connected microchip – robotic organs & of the multiple multidimensional full body – organism connected biological printed organs in quarantine [with new generation machines of PET/MRI on all the surface at the same time, with new generation machines of PET/CT on all the surface at the same time, with new generation machines of high sensitivity perovskite detectors for X-rays & maybe for low-energy G-rays, with all type of new generation machine of Ultrasound Molecular Imaging on all the surface at the same time, with Biopsies, with all types of latest technology microscopes, with mass cytometry, with full tests (blood – excrement – urine – saliva tests & etc) & etc]. Finally, creation of 5 separately vaccines with the safest biochemical substances, with the antibodies (from survivors) & with dead or inactivated the pathogen (in order to awake the immune system), with evolved NK cells [injection into Thymus (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost)], with evolved B-cells [injection into Bone Marrow (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost)] & with evolved killer & helper T-cells [injection into Thymus & Bone Marrow (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) with receptors that recognize the molecule which called MR1, with receptors that recognize the molecules of cancerous EVs & generally all the specific molecules of cancerous & viral cells in order to destroy them] in moderation all of them after in vitro evolution (of them) on full body – organism connected organs-on-chips (from human cells – stem cells & etc) & on full body – organism multidimensional printed organs (from human cells – stem cells & etc) in order to find all the receptors & antibodies which recognize all the cancerous & viral antigens – molecules – submolecules in vivo in order to destroy – eliminate them. These 5 vaccines will help to the confrontation of the diseases – viruses – microbes – parasites – pathogens.
Attainment of immortality: Consolidation of all the Base Editors [CRISPR-CasRx – CHyMErA – ABE8e – ABE8s – Cas-CLOVER – Prime Editing – CRISPR-Cas 13 system (for RNA editing) – irCLASH (for RNA editing) – generally CRISPR-Cas Systems – FluidFM – etc] technologies into one sophisticated technology (which will contain everything) for each function + Evolution of p53 which is the guard of genome (it protects the genome from mutations) + Repairment of double stranded DNA helix via Base Editors, via Rad proteins with their helper proteins generally & via Rad51 with its helper proteins [called Swi5Sfr1 (with evolved yeast cells) & Rad51 paralogs] to awake HR pathway in the repair of DNA double-strand breaks especially, via protein DNA-PK, via protein TEX264 with its enzymes & etc + Induced Pluripotent Stem Cells (from fat) injection on niches (bone marrow, gonads & etc) with control of their specific differentiation, with control at exactly where they needed & with control to the specific quantity that is needed (in moderation) & Transformation of Adult – Old Cells by Reprogramming into Youtful State (into induced pluripotent stem cells) through specific proteins & by Reprogramming all the rest of their Genetic – Biological Material with Gene Drives + Ultrasound for Selective Cancer Cells Death + Selective Telomerase (selective safe number of molecules TERT and TERC that are needed by the organism for the contribution to the selective growth of telomerase level that is better for the organism) only for Healthy Cells & simultaneously Selective Destruction of the Telomerase & Telomeres of all the Cancer Cells + Regulation of Protein eIF5B which contributes to the growth of PD-L1 gene which helps the cancer cells to evade the immune system only when its needed + Selective Cancer Cells Death (Apoptosis) or Selective Differentiation of Cancer Cells into Healthy Cells + Selective Mesophase + Selective Mitosis + Selective number of Cytokines & Selective Cytokinesis + Selective Autophagy [Phagolysosomes (in moderation)] & ER-phagy + Selective Mitochondrial Biogenesis & Selective Mitophagy + Macrophages (activation with curcumin & black pepper) + Microglia (in moderation) + Injection of evolved NK cells [injection into Thymus (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost)], injection of evolved B-cells [injection into Bone Marrow (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost)] & injection of evolved killer & helper T-cells [injection into Thymus & Bone Marrow (with mimetic scaffolds from a safe biomaterial that will be dissolved later in order to give them a boost) with receptors that recognize the molecule which called MR1, with receptors that recognize the molecules of cancerous EVs & generally all the specific molecules of cancerous & viral cells in order to destroy them] in moderation after in vitro evolution (of them) on multiple full body – organism connected organs-on-chips (from human cells – stem cells & etc) & on multiple full body – organism multidimensional bioprinted organs (from human cells – stem cells & etc) in order to find specific receptors & antibodies that recognize all the cancerous & viral molecules in vivo in order to destroy – eliminate them + Mass Bombardment every 3 or 6 months on the organisms with biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations (to all the body at the same time) + Flash radiotherapy (to all the body at the same time) + Ready Safe Vaccines for all the type of diseases (boost of AGO4 & repulsion of AGO4 in a case when a specific virus is needed in order to kill cancer cells) & viruses.
Achievement of regeneration: Scientists should isolate the biological material of regenerating flatworms in order to do selective injections with it to caenorhabditis elegans, drone ants & etc organisms that live for 3-4 weeks in order to have fast results inside from continuous monitoring with tests in order to achieve the immortality up to a point through regeneration. Later, scientists should also do experiments – clinical trials with ill & old humanized mices & generally with ill & old animals which have almost the same genetic – biological material with humans in order to see if regeneration works everywhere before the clinical trials to humans.
Strongest organisms through nutrition: Scientists should evolve all the genetic – biological material via genetics, biochemistry, nanites & all the type of stimulations of all the spores (of vegetables, plants, trees & etc) on the greenhouses & of all the animals on aquacultures & on stables that we need for our consumption in order to prevent them from diseases (for safety reasons) & in order to create better nutrients (for prevention reasons).
Strongest organisms through genetics, biochemistry, nanites & all type of stimulations: Scientists should evolve our DNA – RNA Bases – Letters with Base Editors like CRISPR-Cas systems or like Cas-CLOVER style with all the Cas systems [multiple Cas-9, Cas-12, Cas-13 & etc with their subcategories] & correct all the biological – genetic material’s retinue that will have wrong connections (mutations) of Bases – Letters with Prime Editing, Cas-CLOVER, ChyMErA, ABE8e, ABE8s, CRISPR-CasRx, irCLASH, CRISPR-Cas13 system & generally CRISPR-Cas systems (like Cas9, Cas12, Cas13 & etc with their subcategories) & FluidFM in order to become strongest against diseases, viruses, dangerous microbes, parasites, pathogens & etc. Scientists can also add new Bases – Letters from other organisms on human biological – genetic material’s retinue after safe clinical trials on multiple very ill orangutans – monkeys – apes – chimpanzees – gorillas (to all the organisms that have common biological – genetic material with humans) & to terminally ill volunteers (after an agreement), on multiple full body – organism connected microchip – robotic organs [full body – organism connected human organs-on-chips or human organism-on-chips or human body-on-chips or human-on-chips (from the cells – stem cells – etc of humans)] in quarantine & on multiple multidimensional full body – organism connected biological printed organs (from the cells – stem cells – etc of humans) in quarantine in order to have human organisms new abilities. Finally, scientists must evolve all the other genetic & biological material of human organisms (like double stranded DNA helix), DNA (with its subcategories) & RNA (with its subcategories), cells, stem cells, molecules, submolecules, atoms, subatomic particles & everything other that exist with their subcategories).
Strongest embryos: If there are not ethical problems, scientists should evolve after an agreement all the genetic – biological material of sperms & ovums [via Base Editors (Prime Editing, Cas-CLOVER, ChyMErA, ABE8e, ABE8s, CRISPR-CasRx, irCLASH, CRISPR-Cas 13 system & generally all the CRISPR-Cas systems, FluidFM & etc)] & set gene drives before the fertilization in order to achieve the evolution of embryos & the evolution of their future bloodlines. Scientists should try also to evolve them via biological – light – sound – wave – vibration – pulse – magnetic – electrical – etc stimulations except of the manipulation of their genetic – biological material via Base Editors.
Effort for the resurrection of the deads: If there are not ethical problems, scientists should try to replace after an agreement all the real organs of the deads except of brains with full body – organism microchip – robotic organs or with full body – organism multidimensional printed organs by multidimensional bioprinters & to insert artificial blood which will contain evolved all the genetic – biological material in order to try to bring them back to life from the ice which will remain them unchanged – inalterable. Scientists should try also to create robotic bodies where will connect the brains of the deads in order to awake them through biological – light – sound – ultrasound – wave – vibration – pulse – magnetic – electrical – etc stimulations & bring them back to life until the creation of whole biological or biochemical printed bodies in order to connect them there (the brains).
We are in the point that we can create a new form of life like the Creator of Universe created everything. Behind of every Creation there is a Creator.
Everything of the previous plans should become only after an agreement about ethics & after an agreement with the volunteers – patients – people.
An article by Chaideftos Chaideftos.
Sources
https://www.google.com/
https://scholar.google.com/
https://www.technologyreview.com/
http://news.mit.edu/
https://news.stanford.edu/
https://hms.harvard.edu/news
https://www.broadinstitute.org/
https://wyss.harvard.edu/
https://www.utoronto.ca/news
https://www.anu.edu.au/news
https://www.cam.ac.uk/news
http://www.ox.ac.uk/news-listing
https://news.tsinghua.edu.cn/
http://www.iitd.ac.in/media
https://www.ncbi.nlm.nih.gov/
https://www.nature.com/
https://www.cell.com/
https://www.sciencemag.org/
https://www.nejm.org/
https://www.thelancet.com/
https://jamanetwork.com/
https://www.embopress.org/
https://phys.org/
https://medicalxpress.com/
https://rupress.org/
https://www.genengnews.com/
https://www.embl.org/
https://www.researchgate.net/
https://www.ted.com/
https://www.youtube.com/
https://www.ieee.org/
https://techxplore.com/
https://sciencex.com/news/
https://www.biorxiv.org/
https://arxiv.org/
https://www.mdpi.com/
https://www.hitachi.com/New/cnews/
https://www.wikipedia.org
https://www.utsouthwestern.edu/newsroom/
Try it out
globalisation.gr | Evolution of Organisms | The consolidation of health scientific data will lead to the progress of health science & technology. | [] | [] | [] | 67 |
9,914 | https://devpost.com/software/respirador-com-ventilacao-forca | code for arduino
Built With
hardware | code | protótipo | [] | [] | ['hardware'] | 68 |
9,914 | https://devpost.com/software/colaboracao-e-monitoramento-no-combate-ao-sedentarismo | Inspiration
Melhoria da saúde através de colaboração e monitoramento
What it does
Conecta indivíduos para realização de exercícios em salas virtuais por meio de videoconferência
Monitora os usuários para antecipar possíveis problemas de saúde
How I built it
MVP sendo construído usando react js e API do Google
Challenges I ran into
No tempo disponível no hackaton, ainda não conseguimos finalizar o MVP. A criação de front-end, back-end e integração com as APIs disponíveis vai demandar mais 1 semana de esforço
Accomplishments that I'm proud of
Começamos o desenvolvimento dos aplicativos e, neste momento, conseguimos integrar com as APIs de dispositivos wearables e com as APIs para videoconferência.
What I learned
Dedicar mais tempo para criação do conceito e user story antes de iniciar a criação do MVP.
What's next for Colaboração e monitoramento no combate ao sedentarismo
Assim que integrarmos a solução de videoconferência, lançaremos o MVP e formaremos uma rede de instrutores e alunos
Built With
android
googlefit
webrtc | Colaboração e monitoramento no combate ao sedentarismo | Uso de colaboração de instrutores de saúde e dispositivos de monitoramento para ajudar no combate a problemas de saúde ocasionados pelo sedentarismo. | ['Erik Mattfeldt', 'Ronald Reis', 'Antonio Vinicius Freitas Ferreira'] | [] | ['android', 'googlefit', 'webrtc'] | 69 |
9,914 | https://devpost.com/software/padm-protocolo-de-antissepsia-e-desinfeccao-massiva | O PADM surgiu da percepção da existência de outros antissépticos e desinfetantes, relegados ao esquecimento, bastante efetivos contra os ß-Coronavirus, num momento em que as publicações oficiais limitavam-se a recomendar o álcool 70%, curiosamente o produto mais caro e o menos disponível no Brasil, país que é um dos maiores produtores alcooleiros do mundo.
O PADM traz medidas específicas de proteção para os trabalhadores da saúde que atuam na linha de frente, no atendimento de pacientes positivos para a COVID-19, especialmente nos casos de exposição ocupacional acidental e para a correta inativação dos materiais biológicos contaminados pelo novo Coronavirus.
Além disso, o PADM visa a democratizar e capilarizar o uso de antissépticos e desinfetantes baratos, efetivos, acessíveis a todos e que trazem menos impacto econômico aos cofres públicos, no difícil período de calamidade sanitária.
O próximo passo é o desenvolvimento de estratégias de web marketing, APK e APP que possam levar a toda a sociedade os conhecimentos sobre os antissépticos e desinfetantes efetivos e baratos previstos no PADM, bem como as medidas efetivas de estruturação de barreiras químicas eficazes para proteção contra o n-coronavírus.
Try it out
drive.google.com
www.crfmg.org.br
matheusfcalaca.wixsite.com
1drv.ms | PADM - Protocolo de Antissepsia e Desinfecção MASSIVA | Estratégias (website, web marketing) que possam levar as medidas de antissepsia e desinfecção alternativas, efetivas e baratas, previstas no PADM, à sociedade, para proteção contra o n-CoV-2 | ['Eclésia Cruz', 'Marcelo Crespo', 'matheus calaça', 'Fernando von Gusseck Kleindienst', 'Paulo Alexandre'] | [] | [] | 70 |
9,914 | https://devpost.com/software/healing-frequencies-mix | Electromagnetic frequency healing for coronavirus(covid-19)
Inspiration Audio frequencies mixing
What it does Helps healing of Covid-19.
How I built it Mixing audio frequencies using Mozilla and audacity to record.
Challenges I ran into Choosing the correct frequencies.
Accomplishments that I'm proud of The mix is high quality and all the frequencies can be heard. .
What I learned How to record in high quality sound without distortion of frequencies.
What's next for Healing frequencies mix I hope many people will find it useful to fight the infection.
Built With
audacity
mozilla
Try it out
audiomack.com | Electromagnetic frequency healing for coronavirus(covid-19) | Listen to this mix everyday to reduce the risk of coronavirus infection. | ['Radostin Peev'] | [] | ['audacity', 'mozilla'] | 71 |
9,914 | https://devpost.com/software/smart-ventilators-pq2nwa | Side View Of the final Ventilator Attachment assembly in FUSION 360
Side View Of the final Ventilator Attachment assembly in FUSION 360
Top View Of the final Ventilator Attachment assembly in FUSION 360
Isometric View Of the final Ventilator Attachment assembly in FUSION 360
Isometric view Of the final Ventilator Attachment assembly in FUSION 360
Back View Of the final Ventilator Attachment assembly in FUSION 360
this is the actual 4T arrangement sitting inside the model
Valve with inlet and outlet pipe
Inspiration
As we know the world needs a helping hand in this difficult time period and ventilator shortage is a really big issue across globe. I come from India where we have only 20,000 ventilators for 1.3 billion population which is almost 1 ventilator for every 65,000 people. This condition inspired me to do something for the humanity, since i am doing mechanical engineering I targeted mechanical ventilators and tried to increase its efficiency to the fullest
What it does
I have made and special attachment which can be attached to any ventilator. this attachment is nothing just a simple 4T pipe splitting into 4 at the end which can be attached to the outlet of ventilator to use a single ventilator for multiple patient. Now the hack is that I have attached an unidirectional flow control valve at the ends of these junction this allows us to control pressure in each pipe an also stops cross contamination which enables it to be used in any situation irrespective of the type of patient we have
Also all these flow control valves are connected to micro controller which is further connected to an APP which enables a single doctor to regulate many ventilators and much more patients just through a tap of a button in the app
How I built it
I used Autodesk Fusion 360 to design the 4T pipe and the flow control valve and used the same software for the assembly of the same (4T pipe and unidirectional flow control vale )
Further I have Made and entire assembly which exactly reflects how the real world attachment will look like
I did flow simulations on ANSYS and used ANSYS Fluent tool for taking out computational fluid dynamics of the flow and taking out different pressures and calibrations to achieve a viable scale for the APP
IOT part is done on Arduino micro controller and IOT modules like Node MCU etc for the control of these valve
Making an APP for this setup so that the doctor can control all of them through an APP
Challenges I ran into
TO find appropriate pressure stats for an ventilator and developing perfect calculations for the pressure calculations
Since I am a mechanical engineer so i don't have much knowledge of these IOT although i have made a simple IOT model in Proteus but i wasn't able to make a very good code for the same
The biggest challenge with which i am still struggling is to build the APP due to no knowledge of the APP i am searching for someone who can help me in coding aspects of IOT and building APP part for the project
What I learned
A lot more about fluid dynamics, building equations and getting results out of iy. Tackling new challenges like methods of stopping cross contamination without any additional part . Generating an ideas so that it can meet every aspect like cost, application, etc
What's next for Smart Ventilators
Trying to build a really good APP for it and refining codes for IOT part so as to make the system more and more effective and easy to use
Built With
autodesk-fusion-360
cfd
iot | Smart Ventilators | The idea is to optimize a single ventilator multiple patient system and reduce the need of ventilator assistance doctors by providing an app to control these valve from anywhere any time | ['Akash Pandey'] | ['Wolfram Honorable Mention'] | ['autodesk-fusion-360', 'cfd', 'iot'] | 72 |
9,914 | https://devpost.com/software/segue-o-fluxo | Como funciona
Inspiration
Eu sou um apaixonado por musculação, e sei como o exercício físico é importante para saúde física e mental, e acredito sem dúvidas que nesse momento temos que continuar a praticar exercícios físicos e, a inspiração veio da pergunta, como as academias poderiam continuar de portas abertas evitando aglomerações? A resposta veio... a criação de catracas com controles de fluxos!
What it does
As catracas para controle de fluxo, transmitem em tempo o real o número de alunos que estão em uma determinada academia, conforme as pessoas vão entrando ou saindo das academias, as catracas processam o número de pessoas que estão no local naquele determinado momento e, essas informações são transmitidas ao usuário através de um APP. Isso permitiria ao usuário saber será seguro ir para academia naquele determinado momento, evitando aglomerações, ajudará também os proprietários a terem um maior controle no número de pessoas aumentando também a segurança.
How I built it
A ideia seria as academias terem 4 catracas inteligentes, 2 catracas para sala de espera, sendo uma para entrada e outra para saída, e 2 para sala de musculação, sendo uma também para entrada e outra para saída.
Assim que o aluno passa pela primeira catraca ( todas as catracas são acionadas através de biometria ou cpf do aluno) , o App recebe a informação que uma ou mais pessoas já estão na sala de espera.
Na sala de espera da academia, poderão ser tomadas as medidas de segurança antes do acesso a sala de musculação (Aferir temperatura corporal, utilização de álcool em gel)
Após tomadas as medidas de segurança o aluno passará pela catraca que dá acesso a sala de musculação, a informação de um novo acesso é enviada ao App.
Assim que o número máximo de pessoas na sala de espera e na sala de musculação for atingido as catracas de entradas serão bloqueadas automaticamente, impedindo a entrada de mais pessoas, a catraca será desbloqueada assim que o número de pessoas dentro da sala de espera e da sala de musculação diminua conforme a saída dos alunos. Os proprietários poderão programar o número máximo de pessoas na sala de espera e número máximo de pessoas na sala de musculação, poderão fazer o bloqueio manual para que seja feita uma higienização dos aparelhos.
Já os alunos poderão visualizar o número de pessoas na sala de espera e na sala de musculação, ou se houve uma pausa para higienização e de quanto tempo será pausa.
Challenges I ran into
Sei muito pouco sobre programação, esse é meu maior desafio, porém acredito que após expor a minha ideia, irão surgir as pessoas certas que darão todo suporte para que isso avance
Accomplishments that I'm proud of
Poder participar do Hackcovid19 propondo uma ideia que poderá contribuir para o bem-estar de todos, já é para mim um motivo de orgulho.
What I learned
Que a espécie humana é capaz de se adaptar à diversas realidades e que nesse momento não será diferente se lutarmos e buscarmos novas ideias para ultrapassar os obstáculos!
What's next for Segue o Fluxo!
Espero poder conseguir parceiros para tirar essa ideia do papel, acredito que com a tecnologia que já temos no mercado não encontraríamos dificuldades para implementar o projeto, projeto que com alguns ajustes poderia também se estender a outras áreas como por exemplo, salões de beleza e barbearias. Não tenho duvidas que essa ideia quando colocada em pratica irá ajudar milhares de pessoas a manter a sua saúde física e mental e também manter postos trabalhos e empresas abertas.
Built With
apis
hardware | Segue o Fluxo! | A ideia que proponho traz uma solução para que as academias continuem de portas abertas, outras doenças vieram com o isolamento, obesidade, depressão, diabetes é fundamental mantermos atividade física | ['JEAN PASSOS'] | [] | ['apis', 'hardware'] | 73 |
9,914 | https://devpost.com/software/tele-educacao | INSPIRAÇÃO
Com as suspensão das aulas nas escolas públicas e privadas e com as alternativas de aula on-line, mais uma vez, alunos pobres estão em desvantagem. Sem acesso algum a dispositivos móveis e internet ou sem acesso suficiente a pacotes de dados ou a aparelhos com capacidade para baixar aplicativos, esses estudantes ficam com seu processo de formação comprometido.
DIFERENCIAIS
App com conteúdos exclusivamente da educação básica brasileira.
Colaborativo e gratuito, permite publicar e estudar aulas, textos, exercícios, entre outros.
E, principalmente, viabiliza que estudantes pobres também estude com ele, pois o projeto possui mecanismos para doar tablets com acesso ao app, sem a necessidade do estudante comprar pacotes de dados.
DESAFIO 1
Desenvolver um aplicativo de uso gratuito que possa permitir a livre publicação e utilização de conteúdos pedagógicos da educação brasileira para continuação dos estudos. As possibilidades podem ser: aulas filmadas, textos, exercícios, livros literários ou didáticos, provas de vestibulares e ENEM, jogos e filmes educativos, entre outros.
DESAFIO 1.1
Desenvolver tecnologias para o aplicativo, como:
Divisão do conteúdo postado em: etapas e anos/série (educação infantil, ensino fundamental- 1° ao 9°- e ensino médio - 1° ao 3°), disciplinas (português, matemática...) e conteúdos (adição, citologia, orações coordenadas...).
Controle para bloquear conteúdos fora da proposta e com direitos autorais não autorizados.
Permitir uso on-line e off-line.
Criar ícones:
Início
(com amostras de publicações variadas, inclusive de opções de conteúdos pagos; campo para busca de publicações, conteúdos e outros usuários; sugestões de publicações alinhadas a preferências pré-estabelecidas ou de acordo com o que costuma acompanhar; publicidade; botões para comprar opção premium, com vantagens, ou para fazer doações em dinheiro),
Minha biblioteca
(com as publicações que o usuário escolher colocar na estante virtual),
Publicar
(com campo para o usuário publicar seus conteúdos),
Notificações
(para o usuário ser avisado quanto as novas publicações seguindo suas preferências pré-estabelecidas ou de acordo com o que costuma acompanhar, também para comentários, curtidas, novos seguidores),
Meu perfil
(com os conteúdos publicados pelo usuário, foto de perfil e foto de capa, seguindo, me seguir, seguidores e informações para contato),
Configurações
(configurações de senha, dados pessoais, sobre o aplicativo, ajuda e suporte e logout).
DESAFIO 2
Estruturar mecanismos para arrecadar fundos, a partir do próprio app, para financiar a distribuição de tablets para essa população socioeconomicamente desfavorecida também poder usar o app. Algumas possibilidades podem ser: venda de alguns conteúdos restritos de editoras, produtoras, escolas e cursos particulares. Venda de publicidade, link para doação on-line, patrocínios, apoios e parcerias com órgão públicos e privados. O app deve ser de uso gratuito.
DESAFIO 3
Adiquirir e distribuir dispositivos móveis, como tablets, para os alunos das escolas públicas usarem esse aplicativo de estudos. Algumas possibilidades são: fabricação específica de um modelo simplificado, encomenda ou compra de modelo existente.
DESAFIO 3.1
Estabelecer medidas tecnológicas para que o dispositivo móvel seja utilizado apenas com o aplicativo de estudos. Assim, evita-se mal uso com desvio de função do aparelho, venda e roubo.
DESAFIO 4
Desenvolver estratégias para que o uso da plataforma não dependa de pacotes de dados pagos pelos estudantes. Algumas possiblidades são: parcerias com empresas de telefonia móvel, apoios e patrocínios, compra por parte do projeto.
Try it out
youtu.be | Tele-educação | App para livre publicação de conteúdos da educação. Tem o desafio de financiar a distribuição de tablets para os alunos da rede pública de ensino também usarem o app, sem depender de pacote de dados. | [] | [] | [] | 74 |
9,914 | https://devpost.com/software/ozonetherapy-use-against-covid19-and-in-wellbeing-of-elderly |
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EVALUATION OF THE USE OF A NEW METHOD OF THERAPY FARMACOIMMUNOCEUTICA (O2O3) TO COUNTERACT THE PROGRESSION OF COVID-INFECTION19 AND RESTORE THE CORRECT IMMUNOLOGICAL RESPONSE IN PATIENTS THROUGH THE CONTROL OF ENDOGENOUS MECHANISMS OF IMMUNOREGULATION AND ESPECIALLY THE CELLULAR AND MITOCHONDRIAL MOLECULAR MECHANISMS FUNDAMENTAL TO COUNTERACT INFECTION AND BLOCK ENDOGENOUS RECEPTORS THAT PROMOTE THE GROWTH OF COVID-19 IN AN INFECTED BODY.
For more than 100 years, ozone, considered a virus killer in nature, has been widely used by people for disinfection, sterilization, deodorization, detoxification, storage, and bleaching due to its strong oxidablity. And for this reason, ozone should be adopted as a weapon in the global fight against COVID-19. The OXYGEN OZONE THERAPY, which despite the enormous scientific literature in its favor, is not yet considered in its true potential, turns out to be a very ancient practice and now also studied and validated. It is useful to treat and cure COVID positive patients by treating them by autoemoinfusion of their blood treated with oxygen ozone at a specific concentration. In Germany, Switzerland and other countries, as well as in Italy, it is a common medical practice for many pathological conditions and diseases.
But in history, it has saved thousands of lives in war (especially it has been used by Germans for infected wounds in the pre-antibiotic era) and in Africa and Cuba etc... In China, they have done research immediately and now consider it a potential weapon against CORONAVIRUS.
http://www.china.org.cn/opinion/2020-02/26/content_75747237.htm
Ozone: A powerful weapon to combat COVID-19 outbreak
This project was born in the light of current experimental and clinical knowledge related to the development of COVID-19 infection and physiological biological mechanisms of self-control and new information on the mechanism of action of oxygen ozone therapy. In other words, we have identified the SPIKE and ACE2 cellular receptors that would promote the proliferation of COVID-19 and it is known that these receptors can be blocked with some specific monoclonal but also through the control of NRF2 that blocks the activity of SPIKE and ACE2. Since O2O3 acts on NRF2, it seems very likely that this is the most important physiological mechanism to stimulate to block the endogenous reduplication of COVID-19 by preventing contact with putative receptors of SARS-COVID-19. Treatment with O2O3 has already been tested in many other situations and appears rapid, safe, economical, repeatable and effective. And it has a lot of literature in its favor. Also used and studied by Chinese researchers.
Many Hospitals in Italy use Oxygen Ozone to treat Covid19 positive patients. In Bergamo they observed a great improvement after 5 days of treatment (instead of 15 days) and in Udine Hospital ICU only 1 patient out of 36 is intubated. We would like to propose to treat COVID+ patients by reinfusing their own blood, after contact with oxygen ozone (O2O3). Treatment with O2O3 is in addition to standard therapy in ICU patients suffering from COVID pnaemonitis. We will monitor the effect of O2O3 on the Cytokinic Storm, on the Nrf2 and NFKB and NLRP3 inflammasome and on TOLL LIKE RECEPTOR and APC receptors modulation, and on complement and coagulation cascade. We would like to verify the virucidal action of O2O3 and effect of O2O3 therapy on SPIKE and ACE2 receptors and in the prevention of the need for intubation in treated patients and/or to improve the recovery time of patients based on initial positive experiences.
A statistical analysis will be carried out on the data and the topic will also be treated in a pharmaco-economic perspective, in order to evaluate the aspect connected with the cost/benefit analysis of the treatment.
Inspiration
What's next for OZONETHERAPY USE AGAINST COVID19 AND IN WELLBEING OF ELDERLY
Aims
OBJECTIV: The purpose of our work was to verify the effectiveness of O2O3treatment on the cognitivity and quality of life of patients with cognitive deficits and Alzheimer’s. OxygenOzoneTherapy is
used in medicine since the end of the 19th century for its antibacterial and anti-inflammatory and analgesic effects.
Oxygenozonetherapy induces a controlled oxidative stress with a molecular biochemical nuclear action with a reduction of ROS and an increase of the whole antioxidant physiological system (ARE).
Studies with NIRS and PET of the brain and fRMN showed an improvement in the brain microcirculation and a reactivation of many hypoperfuse zones of the brain after therapy with systemic
oxygenozonetherapy.
Methods
METHODS: we trated 50 patients suffering from MCI with O2O3 therapy. We treated our patients with an autohemoinfusion of their blood treated with oxygenozone and we measured the quality of
life and cognition using specific scales.
Results
RESULTS: Our experience in 50 MCI patients with MCI has shown a marked improvement in MMSE by an average of four points and cognitivity compared to untreated Pts. Also improved autonomy
and spatial orientation and sleep with disappearance of sleep disorders and improved relationship with caregiver. For this reason, the Italian Ministry of Health has approved the treatment with
O2O3 in cognitive deficiency and we propose to extend this treatment not expensive, feasible, free from complications in dementia patients.
Conclusions
O2O3therapy is safe and effective causing the activation of Nrf2 increasing ARE lowering Nfkb. Inhibits the production of APP/aβ in the brain and improves cognitivity in a transgenic mouse (2019).
Built With
any | OZONETHERAPY USE AGAINST COVID19 AND IN WELLBEING OF ELDERLY | O2O3 is a positive therapeutic procedure very useful in many diseases and in particular in controlling infections, improving immune system and cognitivity of patients, in particular in elderly. | ['giovanni-ricevuti'] | [] | ['any'] | 75 |
9,914 | https://devpost.com/software/mobilecovideshopper | Alert tab - Community members can Alert their community
Find Tab - Community members can find items that are in need
Stores Tab - Search for stores e.g type vegan or burger or market
Inspiration
The inspiration for this project comes from the need to support the community during this crisis and manage the potential shopping panic, where consumers can easily find goods they need. If the situation gets worse, it would be nice for people to find what they are looking for by easily using this app.
What it does
The app informs and alerts people when a certain item becomes available, it predicts when the item will be ready in good quantity, allowing people to obtain it promptly. It should eventually reduce the amount of time people have to spend moving around and therefore limit the scope for cross-infection. Displays the number of people on the queue. It updates on a daily basis.
How I built it
Using React Native I created the app that communicates with a Node Rest API. The app has 4 tabs one is the Home tab, that lists three sections.
Tab 1 - Find
Benefits
Safer travel by reducing the journey time
Reduce the chances of cross-infection by travelling less
Easily find out if the place we wan that have the goods you require within your location
Tab 2 - Alert
Benefits
Easily add the store where you found missing goods while saving your anonymity.
Data is saved to the database that is then used by other users in your community.
It helps you locate the store that you are in.
Tab 3 - Stores
Benefits
Find the stores that are close to you by typing keywords for example vegan or market or fish
The map will show you which stores are near to you.
Challenges I ran into
Learning React Native understanding how it works fixing issues to make the app work in different devices.
Accomplishments that I'm proud of
Learnt something new in the last two weeks but also if it is used could help a lot of people in the community.
What I learned
React Native and how to use it to make Native apps
What's next for MobileCovideshopper
Kepp learning and making it better.
Built With
node.js
prisma
react
reactnative
yeld
Try it out
github.com | CovidShopper Mobile | A mobile app that helps shoppers during the pandemic | ['Aris Markogiannakis', 'Lucy Ernest', 'Rena .', 'Hal Saleh'] | [] | ['node.js', 'prisma', 'react', 'reactnative', 'yeld'] | 76 |
9,914 | https://devpost.com/software/covnatic-covid-19-ai-diagnosis-platform | Landing Page
Login Page
Segmentation of Infected Areas in a CT Scan
Check Suspects using Unique Identification Number (New Suspect)
Check Suspects using Unique Identification Number (Old Suspect)
Suspect Data Entry
COVID-19 Suspect Detector
Upload Chest X-ray
Result: COVID-19 Negative
Upload CT Scan
Result: Suspected COVID-19
Realtime Dashboard
Realtime Dashboard
Realtime Dashboard
View all the Suspects (Keep and track the progress of suspects)
Suspect Details View
Automated Segmentation of the infected areas inside CT Scans caused by Novel Coronavirus
Process flow of locating the affected areas
U-net (VGG weights) architecture for locating the affected areas
Segmentation Results
Detected COVID-19 Positive
Detected Normal
Detected COVID-19 Positive
Detected COVID-19 Positive
GIF
Located infected areas inside lungs caused by the Novel Coronavirus
Endorsement from Govt. Of Telengana, Hyderabad, India
Endorsement from Govt. Of Telengana, Hyderabad, India
Generate Report: COVID-19 Possibility
Generate Report: Normal Case
Generated PDF Report
Inspiration
The total number of Coronavirus cases is
2,661,506 worldwide
(Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and rapid testing is the only option to battle with the virus. McMarvin took this opportunity as a challenge and built AI Solution to provide a tool to our doctors. McMarvin is a DeepTech startup in medical artificial intelligence using AI technologies to develop tools for better patient care, quality control, health management, and scientific research.
There is a current epidemic in the world due to the Novel Coronavirus and here
there are limited testing kits for RT-PCR and Lab testing
. There have been reports that kits are showing variations in their results and false positives are heavily increasing.
Early detection using Chest CT can be an alternative to detect the COVID-19 suspects.
For this reason, our team worked day and night to develop an application which can help radiologist and doctors by automatically detect and locate the infected areas inside the lungs using medical scan i.e. chest CT scans.
The inspirations are as below:
1. Limited kit-based testings due to limited resources
2. RT-PCR is not as much as accurate in many countries (recently in India)
3. RT-PCR test can’t exactly locate the infections inside the lungs
AI-based medical imaging screening assessment is seen as one of the promising techniques that might lift some of the heavyweights of the doctors’ shoulders.
What it does
Our COVID-19 AI diagnosis platform is a fully secured cloud based application to detect COVID-19 patients using chest X-ray and CT Scans. Our solution has a centralized Database (like a mini-EHR) for Corona suspects and patients. Each and every record will be saved in the database (hospital wise).
Following are the features of our product:
Artificial Intelligence to screen suspects using CT Scans and Chest X-Rays.
AI-based detection and
segmentation & localization of infected areas inside the lungs
in chest CT.
Smart Analytics Dashboard
(Hospital Wise) to view all the updated screening details.
Centralized database (only for COVID-19 suspects) to
keep the record of suspects and track their progress
after every time they get screened.
PDF Reports,
DICOM Supports
, Guidelines, Documentation, Customer Support, etc.
Fully secured platform
(Both On-Premise and Cloud)
with the privacy policy under healthcare data guidelines.
Get Report within Seconds
Our main objective is to provide a research-oriented tool to alleviate the pressure from doctors and assist them using AI-enabled smart analytics platform so they can
“SAVE TIME”
and
“SAVE LIVES”
in the critical stages (Stage-3 or 4).
Followings are the benefits:
1. Real-world data on risks and benefits:
The use of routinely collected data from suspect/patient allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world.
2. Studies can be carried out quickly:
Studies based on real-world data (RWD) are faster to conduct than randomized controlled trials (RCTs). The Novel Coronavirus infected patients’ data will help in the research and upcoming such outbreak in the future.
3. Speed and Time:
One of the major advantages of the AI-system is speed. More conventional methods can take longer to process due to the increase in demand. However, with the AI application, radiologists can identify and prioritize the suspects.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. DESKTOP GUIs like Tkinter
5. Docker and Kubernetes
6. JavaScript for the frontend features
7. DICOM APIs
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 2000 medical scans i.e. chest CT and X-rays of 500+ COVID-19 suspects around the European countries and from open source radiology data platform. We then performed validation and labeling of CT findings with the help of advisors and domain experts who are doctors with 20+ experience. You can get more information in team section on our site. After carefully data-preprocessing and labeling, we moved to model preparation.
2. Model Development:
We built several algorithms for testing our model. We started with CNN for classifier and checked the score in different metrics because creating a COVID-19 classifier is not an easy task because of variations that can cause bias while giving the results. We then used U-net for segmentation and got a very impressive accuracy and got a good IoU metrics score. For the detection of COVID-19 suspects, we have used a CNN architecture and for segmentation we have used U-net architecture. We have achieved 94% accuracy on training dataset and 89.4% on test data. For false positive and other metrics, please go through our files.
3. Deployment:
After training the model and validating with our doctors, we prepared our solutions in two different formats i.e. cloud-based solution and on-premise solution. We are using EC-2 instance on AWS for our cloud-based solution.
Our platform will only help and not replace the healthcare professionals so they can make quick decisions in critical situations.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself.
One of the challenge is “Validated data” from different demographics and CT machines.
Due to the lockdown in the country, we are not able to meet and discuss it with several other radiologists. We are working virtually to build innovative solutions but as of now, we are having very limited resources.
Accomplishments that we're proud of
We are in regular touch with the State Government (Telangana, Hyderabad Government). Our team presented the project to the Health Minister Office and helping them in stage-3 and 4.
Following accomplishments we are proud of:
1. 1 Patent (IP) filled
2. 2 research paper
3. Partnership with several startups
4. In touch with several doctors who are working with COVID-19 patients. Also discussing with Research Institutes for R&D
What we learned
Learning is a continuous process. Our team learnt
"the art of working in lockdown"
. We worked virtually to develop this application to help our government and people. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for M-VIC19: McMarvin Vision Imaging for COVID19
Our research is still going on and our solution is now endorsed by
the Health Ministry of Telangana
. We have presented our project to
the government of Telangana for a clinical trail
. So the next thing is that we are looking for trail with hospitals and research Institutes. On the solution side, we are adding more labeled data under the supervision of Doctors who are working with COVID-19 patients in India. Features like
Bio-metric verification, Trigger mechanism to send notification to patients and command room
, etc are under consideration. There is always scope of improvement and AI is the technology which learns on top of data. Overall, we are dedicated to take this solution into real world production for our doctors or CT and X-rays manufacturers so they can use it to fight with the deadly virus.
Built With
amazon-web-services
flask
google-cloud
javascript
keras
nvidia
opencv
python
sqlite
tensorflow
Try it out
m-vic19.com | M-VIC19: McMarvin Vision Imaging for COVID19 | M-VIC19 is an AI Diagnosis platform is to help hospitals screen suspects and automatically locate the infected areas inside the lungs caused by the Novel Coronavirus using chest radiographs. | [] | ['1st Place Overall Winners', 'Third Place - Donation to cause or non-profit organization involved in fighting the COVID crisis'] | ['amazon-web-services', 'flask', 'google-cloud', 'javascript', 'keras', 'nvidia', 'opencv', 'python', 'sqlite', 'tensorflow'] | 77 |
9,914 | https://devpost.com/software/covid-19-detect-ii | DULI em ação
Dataset de TESTE
DORES. O esgarçamento da saúde pública e privada.
- DORES --> SUBNOTIFICAÇÃO <-- + DORES
DULI Teste IMAGEM SIEMENS
Classificação de imagem e detectção de lesões
PITCH & MKT
DULI em ação
BP
Dataset TESTE
DULI em ação
CLASSIFICAÇÃO POR PIXEL
Dataset de TESTE
Dataset de TREINO
Expansão orgânica DULI por conta da correlação patológica
Parceira VMI
Parceira VMI
Parceira VMI
Parceira VMI
Parceira VMI
Parceira VMI
Atualização: Parceira comercial com a VMI
Atualização: Participando do Rad19. Elevada Acurácia vx Modelo Multipatológico.
Teste DULI com incremento de dois dataset de treino Rad19.
Fica claro que modelos multipatológicos são o presente e futuro por conta da correlação patológica.
inspiração
- solução para cenário de Sindemia e não Pandemia;
- imunopatológico;
- criança de cinco anos entende e usa
- não especialista entende e usa
- não cientista entende e usa
- seletivo;
- sensível;
- barato;
- simples;
- não invasivo
- UX UI matador
- killer APP
o que faz
- plataforma de Inteligência Artificial (Deep Learning)
- aprendeu através de análise de raios X e tomografias
- quais são os padrões visuais que conseguem apontar casos como:
- COVID-19, SARS e Y outras doenças com grau de acerto de 80%.
como nós construímos
- selecionamos plataforma de IA Profissional - TensorFlow - aplicado em ferramentas de IA para crianças
- Teachable Machine.
- selecionamos datasets estrangeiros. inexistentes no Brasil(dor - opoertunidade):
- CanalSandeco
- ieee8023/covid-chestxray-dataset
- COVID-Net Open Source Initiative
- COVID-CT-Dataset: A CT Scan Dataset about COVID-19
- National Institutes of Health
- JHU CSSE COVID-19 Data set.
- TREINO modelo DULI
- incluímos multiplos datasets patológicos para treino:
- sars
- pneumocistose
- pneumonia aspiração
- pneumonia cavitante
- pneumonia-clamídia-L
- pneumonia por Klebsiella
- pneumonia legionella
- pneumonia pneumococcal
- pneumonia pneumocystis carinii
- pneumonia pneumocystis jirovecii
- pneumonia pneumocystis
- pneumonia Streptococcus
- NORMAL
- Pneumonia
- Covid-19 ARDS
- Covid-19 & Pneumonia
- Covid-19 Tomografia Computadorizada
- Não Covid-19 Tomografia Computadorizada
- Covid-19
- NIMG*
- * NÃO IMAGEM quando a leitura real time por webcam
- fixo
- mobile
- treinamos o DULI com dados classificados pela plataforma do Ministério da Saúde
- Indeterminado COVID-19 ---> Resultados: covid-19, pneumonia, sars
- Atípico COVID-19 ---> Resultados: covid-19, pneumonia, sars
- Típico COVID-19
- TESTE modelo DULI Indeterminado COVID-19 ---> covid-19, pneumonia, sars,...,..
- TESTE modelo DULI Atípico COVID-19 ---> covid-19, pneumonia, sars,..,..
desafios que encontramos
- inexistência de data sets classificados de pacientes brasileiros para treino do modelo DULI no Brasil.
realizações das quais nos orgulhamos
entregar mvp app DULI funcional
vc tem uma imagem de raio x ai !?
click e testa aqui no
DULI
ou aponte seu celular para o QRCode do DULI
não tem uma imagem?
aponte para o QRCode e pegue no Ministério da Saúde
o que nós aprendemos
- possível
- viável
- rentável
- mudar cenário histórico de:
- `vírus matam menos que erros :
- humanos
- médicos
- políticos
- religiosos.
- ontem
- agora
- menos amanhã
próximos passos
- estruturar a Fodha Foundation - implantar na indústria de equipamentos médicos o protocolo fodha
- full open dataset health - human & animal
- estruturar a Fodha inc.
- estruturar o mellieri Human hub
- hospitais
- universidades
- clínicas
- institutos de pesquisas
- indústria de equipamentos médicos
- gov
- ongs
- ampliar|entregar|estruturar|organizar
- data set global de treino
- data set global de teste
- treinar o modelo DULI em todas patologias por imagens, incluindo câncer.
- treinar o modelo DULI em todas patologias por todos inputs, incluído ECG
- detectar insuficiência cardíaca num único batimento.
- classificar os 80% de óbitos italianos com problemas cardíacos em
- grupo de risco
- efeito pós COVID-19
- identificar COVID-19 em outros órgãos como coração e rins, por exemplo.
- parceria com NLCC em função da demanda por processamento.
- parceria com AWS privados em função de demanda por processamento.
- entregar
- unidades móveis de teste por imagem
- POPRua
- Periferia Sem Corona
- outros vulneráveis
- RBDULI : Ram Bitcoin - DULI. Dados e processamento distribuído sob
- Cloud Mermory Ram de todo o mundo sob smartcontract treinando
- infinitamente
- Parceria Mipasa
- Atualização: Julho de 2027, parceria comercial com VMI empresa do Prime Holding
- No Inrad RadVid19 Acurácia ROC 0,995
- Pós api hack elo & hackatowns paysmart elo 2020 -->conta digital com créditos uso. Findo, add cripto ativo plimm, nossa cripto moeda.
Built With
github
googlecolab
googleserver
kaggle
keras
python
teachablemachine
tensorflow
Try it out
cutt.ly
cutt.ly
www.kaggle.com | Humanizare [Duli] | subnotificação:ZERO | ['zeh sobrinho', 'Eduardo Nery'] | [] | ['github', 'googlecolab', 'googleserver', 'kaggle', 'keras', 'python', 'teachablemachine', 'tensorflow'] | 78 |
9,914 | https://devpost.com/software/d056-ambiente-virtual-fiocruz-app-e-webapp | Contato
AGRADEÇO A TODOS PELO APOIO!
SEGUE VIVO O DESAFIO.
Ambiente virtual de trabalho, assistência, pesquisa e informação da FIOCRUZ (App e Web App) para trabalhadores da Saúde (tanto na linha de frente quanto na continuidade dos serviços do SUS, hoje tão afetados pela pandemia) prestarem seus serviços junto aos usuários do SUS, trocarem suas experiências e definirem através do controle de versões (voip, videoconferência dentre outras tecnologias, poderemos detalhar) protocolos determinantes para:
Prevenir o contágio, combater a doença, reduzir a mortalidade por Covid-19 (e outras em consequência do distanciamento, quarentena e sobrecarga dos sistemas de saúde), prestar o serviço de telemedicina e telessaúde nas várias especialidades hoje impedidas por estarem afetadas pela pandemia, levantar evidências, informar a população. Neste mesmo ambiente, trabalhadores, pesquisadores e usuários poderão coletar e relatar evidências partindo de uma base/repositório único. Justificativa do Desafio
A FIOCRUZ, com o seu eminente papel nesta epidemia reconhecido pela OMS, carece de Ferramenta digital que se aproxime do trabalhador/pesquisador/cidadão (hoje um dos principais vetores do Sars-cov 2) e os instrua em nível informacional de forma integrada e concomitante. Tendo um papel tão importante num momento sanitário ímpar, torna-se contraproducente e moroso para eficácia no combate a pandemia ter que compilar todas as informações para mitigar os efeitos da doença, produzir ciência, avaliar notícias falsas e manter pleno o cumprimento de todos as entregas, princípios e diretrizes do SUS, pois parte de suas atividades também encontra-se afetada pela pandemia.
A proposição deste desafio no HACKCOVID19 ou em outra chamada poderá proporcionar a sugestão de produtos das equipes competidoras que trarão ferramentas com foco em informações centralizadas do público alvo da pandemia e voltada a ele, de forma automatizada, evitando incerteza e diminuindo a necessidade de consultar outras bases de dados/informações, uma vez que os dados estarão centralizados neste ambiente.
Built With
ciencia-de-dados
db
java
javascript
python | D056 - Ambiente Virtual FIOCRUZ - APP E WEBAPP | Ferramenta digital que se aproxime do trabalhador/pesquisador/cidadão (hoje um dos principais vetores do Sars-cov 2) e os instrua em nível informacional de forma integrada e concomitante. | ['Thiago Muniz'] | [] | ['ciencia-de-dados', 'db', 'java', 'javascript', 'python'] | 79 |
9,917 | https://devpost.com/software/ops_brew | Enabling logs to send to multiple tools
Filtering Data
Create alerts
Monitoring dashboard
Measure the data flow
Inspiration
Challenges associated with traditional log management and the evolution of the cyberattack landscape which demanded a Centralised Log Management solution to easily build pipelines to collect and stream logs.
Democratizing the ability to create log pipelines to even users with low technical skills.
Overcome the bandwidth issues associated with multiple agent installation.
Operational overhead of management of multiple log gateways/agents.
What it does
A self-service GUI based platform for building and maintaining log collection, filtering, masking, and redirection pipelines facilitating log streaming from multiple sources to multiple destinations including Azure Sentinel. In simple terms, it aggregates logs from disjointed systems to advanced platforms like Sentinel.
Kubernetes native CLM platform enabling deployment to any environment of choice*.
It also helps to mutate sensitive data and additional actions (such as deleting a record from a log), some of the supported sensitive data examples are below
Personally identifiable data.
Health Data
Financial Data (like credit card numbers)
Passwords
IP addresses may be considered sensitive, especially when in combination with personally identifiable data
How we built it
We built it as a Kubernetes native app.
We leveraged k8s APIs and we chose golang to build the platform.
Various open-source tooling was integrated to be able to seamlessly collect, stream, monitor logs.
Challenges we ran into
Encrypting logs in transit
Building efficient monitoring dashboard for sanity/quality check
Connecting k8s cluster from multiple providers
Accomplishments that we are proud of
One agent to collect logs from multiples sources and send that to multiple destinations
Reduced total bandwidth consumption for log data traffic
Inbuilt monitoring and alerting capability for health check of log-collector
Agentless log collection
K8s native multi-environment deployment
Work's well with a hybrid environment
What we learned
Logging best practices
Multiple log formats(CEF, LEEF, Syslog, Json, XML etc.)
How CLM can be build to complement SIEM for better threat analysis
What's next for Ops_brew
Multi K8s environment support
Capturing of network flow logs
Enabling more sources(IT/OT)
Creating more workbooks for all sources
Ops_brew with Azure Sentinel scenarios
Here we are categorizing the scenarios on how Ops_brew can accelerate the adoption of Azure Sentinel.
Explorer
For customers on the lookout to invest in a new SIEM solution or renew an existing license, Azure Sentinel is a future proof solution considering the fact that it natively supports cloud workloads and not to mention its easier to implement as does not have the heavy CAPEX investment associated with traditional SIEM. SIEM solutions need logs from source systems to be effective, Ops_brew enables quick creation and deployment of pipelines from hybrid sources to Azure Sentinel.
Achiever
For customers who have already procured Enterprise SIEM, generally have limited use-cases built and do not have integrations for cloud workloads. Ops_brew can direct logs from the cloud and on-prem sources to Azure Sentinel and other SIEM solutions.
Master(Mostly MSP)
Managed Security Providers would have ideally made significant investments in tools and processes to offer SoC services to multiple customers. Ops_brew can enable such a team to redirect logs to their existing tools and to Azure Sentinel, leveraging it as a secondary SIEM.
Built With
angular.js
golang
kubernetes
microservice
prometheus
Try it out
console.opsbrew.com | Ops_brew | Codeless log pipeline management. A self-service GUI based and K8s native platform facilitating of log streaming from multiple sources to multiple destinations | ['ASHMIL HUSSAIN K', 'Rajat Chitgupi', 'Nihil Babu', 'Sarath Chandran', 'Vishnu KS', 'saikrishnan s', 'Arjun Shaji', 'Jay Krishnan', 'Abhiram Vijayan', 'Arun Mohan'] | ['First Place'] | ['angular.js', 'golang', 'kubernetes', 'microservice', 'prometheus'] | 0 |
9,917 | https://devpost.com/software/gopuff-s-sentry-platform | goPuff Sentry Platform Architecture
goPuffs Sentry Platform
Serverless incident response platform to detect and alert on network and communication infrastructure
Inspiration
As a startup, it is difficult to hire (
afford
) experienced security engineers and analysts. Due to the pandemic, our company was further challenged to optimize our security team. Following the leadership of our Engineering department, the goPuff Security Team architected a serverless Cloud Infrastructure which allowed our company to be nimble and flexible. This shared responsibility model allowed goPuff to focus on growing the business and focus on customer happiness.
By making these architecture decisions early, allowed goPuff leadership to mature our engineering team and implement a zero trust model.
What it does
goPuff's Sentry Platform is designed to consume, transform, and alert on serverless infrastructure by using serverless services. goPuff's Sentry Platform is designed to alert on third-party cloud infrastructure that will help detect remote work force abuse, facility network abuse, and proactively identify systems that are misconfigured and remediate.
The current iteration of the goPuff's Sentry Platform is to design use cases to protect two main Cloud Infrastructure components:
Slack Enterprise
Cisco Meraki Networks
Slack Enterprise
Paying for a Data Loss Protection (DLP) solution is an option, but that takes time and can be expensive. As the startup grew, process and technical debt was inevitable. To help with that, we have focussed on some use cases to tackle those areas
Use Case
: High Number of Downloads within past two weeks of sensitive channel
Description
: An account could be blocked if the user is downloading a high volume of sensitive files. This file has a handful of business level information that should not be continuously downloaded
Use Case
: Slack Filename Keyword Sniffer
Description
: An account could be blocked if the user triggers a high volume of keyword triggers
Use Case
: Maximum Daily Download
Description
: An account could be blocked if there are doing heavy downloads. This could be a rapid data dump through Slack
Use Case
: Login attempt by Blocked MFA user
Description
: An IP could be blocked if there are too many logins or attempts against a single IP
Cisco Meraki Networks
As a startup, having a Managed Service Provider (MSP) can be rewarding and challenging. This use case helps us identify when our ISP's SD-WAN LTE backup activates to alert our incident response team to update the facility network configuration
Use Case
: Identify Public IP Change
Description
: Trigger an alert to incident response team to verify SD-WAN LTE backup is active and force business approved devices to only function on network to save on bandwidth utilization
How we built it
The goPuff Security Team focussed on building this platform with serverless components with no virtual machines to allow our platform to be refactored in the future.
Data Connector(s)
The goPuff Security Team designed the Sentinel Log Ingestion Format to utilize the REST API. This allowed our stack to utilize serverless services for collection and offload the Extract, Transform, Load (ETL) layer to a container (
utilizing Logstash
)
Slack Enterprise Collector
:
Collector Service
:
Timer Trigger for Azure Functions
to monitor the Slack Audit Logs API:
Slack Enterprise Audit Logs
Description
: Timer Trigger fires every minute collecting specific Slack Audit actions and posts to an
Azure Event Hub
Azure Monitor Data Collector API (ETL Layer)
: Build and deploy a container on
Azure Container Instance (ACI)
service with
Logstash
.
Logstash
connects to
Azure Event Hub
(
Extract
), filters the data that is needed (
Transforms
), and utilizes the Azure Monitor Data Collector API (
Load
) to send to
Azure Sentinels Log Analytics
Workspace
Cisco Meraki Collector
:
Collector Service
:
Timer Trigger for Azure Functions
:
Description
: Timer Trigger fires every 30 minutes collecting the following API device endpoints and posts to an
Azure Event Hub
List the devices in an organization
Return the uplink information for a device
Azure Monitor Data Collector API (ETL Layer)
: Build and deploy a container on
Azure Container Instance (ACI)
service with
Logstash
.
Logstash
connects to
Azure Event Hub
(
Extract
), filters the data that is needed (
Transforms
), and utilizes the Azure Monitor Data Collector API (
Load
) to send to
Azure Sentinels Log Analytics
Workspace
Deployment Strategy
The goPuff Security Team utilized the following CI/CD deployment flow using Azure DevOps
Stages:
Stage
:
Build Container
Job
: Build and Push container to Azure Container Registry (ACR)
Stage
:
Delete Container Group
Job
: run an
inlineScript
to delete resource group container group
Stage
:
Deploy Container Azure Resource Manager (ARM) Template
Job
: Deploy Logstash container with
Azure Storage Account Volume Mount
via ARM Template inside a Azure Subnet
This allowed us to securely deploy a Logstash config by Enabling a TLS endpoint in a sidecar container
Stage
: `Build Function App Service
Job
: Build, Archive, Copy, and Publish Timer Trigger Azure Function to Azure Subnet
Stage
:
Deploy Azure Function App Service to Azure Subnet
Job
: Download, Deploy, Stage Azure Function artifact into Azure Subnet
Playbooks
The playbooks provide the end user with both notification and actions strategies that leverage the Slack APIs. When a playbook alert is triggered, a Slack channel monitored by goPuff Incident Response can action on the alert within Slack. This allows us to abstract staff from working in Azure for simple incidents. This has improved workflow automation and faster mitigation of events
Note
:
any secret values or identifiers have been removed for security purposes, but the contextual strategy is transparent
Challenges we ran into
Costs
When first designing this model, the goPuff Security Team had to be resourceful on the amount of logs that were going to be ingested due to tight budgets due to COVID-19. This was a bit difficult at first for the team as they were learning the mechanics of Azure Sentinel and had limited experience with the ETL process
Skillset
The goPuff security team is lean, so when working on use cases most of the staff were newer to Security Information and Event Management (SIEM) technology. There was a week learning curve on what to action on for most of the platforms. As we start to bring in more Incident Responders, we expect the same learning curve when trying to create newer use cases in the future
ARM Development
When creating the ARM to deploy containers, there is very minimum verbose debug logging available during deployment. The goPuff Security team got stuck on the
Azure Storage Account File Share Service connection
. Whenever a misconfigured ARM was deployed, there was a 30 minute delay for the File Share Service to fail. This caused multiple hours of troubleshooting before we identified the misconfigured string.
Accomplishments that we're proud of
Infrastructure-as-Code (IaC)
How we designed and able to deploy the full infrastructure in less than 10 minutes for any new code or container deployment. This allows us to identify new use cases and have a working environment quickly
Team Building
This project allowed our goPuff Security Team to build multiple skill sets across goPuff verticals. This empowered engineers to think about security risk in a different way to not only protect Infrastructure, but understand business risk to platforms
What we learned
Azure Sentinel can be utilized in multiple ways outside of normal security functions. The goPuff Security Team was able to identify a new method to detect business risks. This new method can help automate simple tasks allowing our Incident Response team to focus on more pressing tasks. By triggering the playbook functionality, this freed up staff and provided goPuff with a method to proactively remediate process with Azure Logic Apps.
What's next for goPuff's Sentry Platform
Azure Kubernetes Service (AKS)
The goPuff Security Team has identified some ACI limitations in our stack which is going to force us to move to AKS for most of our platform. This will also let us build manifests to focus on moving functionality to other clouds, but still utilize the raw power of Azure Sentinel as a SIEM
Durable Function Development
The goPuff Security team loves Logstash, but there is some limitations with the Output plugin. To figure out how to work around this, we might invest development time to rewrite a new method to write with the
Azure Monitor Data Collector API
.
Syslog Ingest Layer
Once we stand up our AKS layer, the goPuff Security Team will be deploying a Syslog ingest layer to allow our network equipment to push data instead of pulling via the API. This will allow us to consume our MSP's router and firewall logs into our environment to help with proactive remediation
Built With
apim
containers
event-hub
javascript
logstash
serverless
Try it out
github.com | goPuff's Sentry Platform | Serverless incident response platform to detect and alert on network and communication infrastructure | ['Chris Maenner', 'Joseph Rivera', 'DamionWaltermeyer'] | ['Runner Up'] | ['apim', 'containers', 'event-hub', 'javascript', 'logstash', 'serverless'] | 1 |
9,917 | https://devpost.com/software/midas-5fw93u | Inspiration
Anomaly detection in graphs is a critical problem for finding suspicious behavior in innumerable systems, such as intrusion detection, fake ratings, and financial fraud. This has been a well-researched problem with the majority of the proposed approaches focusing on static graphs. However, many real-world graphs are dynamic in nature, and methods based on static connections may miss temporal characteristics of the graphs and anomalies.
Among the methods focusing on dynamic graphs, most of them have edges aggregated into graph snapshots. However, to minimize the effect of malicious activities and start recovery as soon as possible, we need to detect anomalies in real-time or near real-time i.e. to identify whether an incoming edge is anomalous or not, as soon as we receive it. In addition, since the number of vertices can increase as we process the stream of edges, we need an algorithm which uses constant memory in the graph size.
Moreover, fraudulent or anomalous events in many applications occur in microclusters or suddenly arriving groups of suspiciously similar edges e.g. denial of service attacks in network traffic data and lockstep behavior. However, existing methods which process edge streams in an online manner aim to detect individually surprising edges, not microclusters, and can thus miss large amounts of suspicious activity.
What it does
MIDAS, short for Microcluster-Based Detector of Anomalies in Edge Streams, detects microcluster anomalies, or suddenly arriving groups of suspiciously similar edges, in edge streams, using constant time and memory. MIDAS uses unsupervised learning to detect anomalies in a streaming manner in real-time and has become a new baseline. It was designed keeping in mind the way recent sophisticated attacks occur. MIDAS can be used to detect intrusions, Denial of Service (DoS), Distributed Denial of Service (DDoS) attacks, financial fraud and fake ratings. In addition, by using a principled hypothesis testing framework, MIDAS provides theoretical bounds on the false positive probability, which earlier methods do not provide. Also, MIDAS is up to 55% more accurate while being up to 929 times faster than state of the art approaches.
Features
Finds Anomalies in Dynamic/Time-Evolving Graph: (Intrusion Detection, Fake Ratings, Financial Fraud)
Detects Microcluster Anomalies (suddenly arriving groups of suspiciously similar edges e.g. DoS attack)
Theoretical Guarantees on False Positive Probability
Constant Memory (independent of graph size)
Constant Update Time (real-time anomaly detection to minimize harm)
Up to 55% more accurate and 929 times faster than the state of the art approaches
How I built it
MIDAS finds anomalous edges from a dynamic graph in a streaming manner. It combines a chi-squared goodness-of-fit test with the Count-Min-Sketch (CMS) streaming data structures to get an anomaly score for each edge. MIDAS also incorporates temporal and spatial relations to achieve better performance.
Challenges I ran into
Trying to detect anomalies/intrusions in real-time as soon as the edge/communication arrives. This has to be done in constant memory.
Accomplishments
450+ stars on the
Github Repository
.
MIDAS was featured as a top story on
KDnuggets
and
Hacker News
.
MIDAS was covered by
AIhub
,
ACM TechNews
,
Towards Data Science
,
Towards AI
,
Analytics India Magazine
,
MarkTechPost
,
insideBIGDATA
,
MarTech
,
AI Trends
MIDAS implementations in C++, Golang, Python, Java, Ruby, Rust, R and Julia.
Multiple cybersecurity and e-commerce firms want to fine tune MIDAS for their requirements.
What I learned
Streaming Anomaly Detection, cybersecurity, threat detection
What's next for MIDAS
Deploy within Azure Sentinel
Distributed version
Hardware implementation
Extend to multi-attributed graph and record setting
Apply in Knowledge Graphs
Built With
c++
Try it out
github.com | MIDAS | MIDAS finds anomalies, intrusions, DoS attacks, financial fraud, fake ratings on dynamic graphs in real-time and streaming manner while taking constant memory. https://github.com/Stream-AD/MIDAS | ['Siddharth Bhatia'] | ['Popular Choice'] | ['c++'] | 2 |
9,917 | https://devpost.com/software/azure-sentinel-project | Architecture Diagram
Hunting Query for Slack
List of Hunting Queries for Slack
Analytics Rules for Slack
Dashboard
Poster
Inspiration
Many organizations use Slack and Microsoft Teams for secure collaboration across teams, departments and offices.
Azure Sentinel
can be used by security teams at these organizations to secure and monitor Slack.
What it does
One of the great features of Azure Sentinel is its ability to ingest and analyze data from any source not just from Microsoft products. Our project is an end-to-end solution to enable enterprises that use slack onboard to Azure Sentinel.
Our Project is made up of:
Log Agent
Azure Sentinel Detections and Hunting Queries
Log Agent collects logs from Slack and ingests them into
Azure Sentinel Log Analytics WorkSpace
. Setup script deploys Log Agent as a Cron Job that runs at intervals defined by the user. You can also setup the Log agent in Azure VM. On Windows machine, you can run setup the file 'setup.py' as a scheduled task.
After the data is available in
Azure Sentinel Log Analytics WorkSpace
, cybersecurity experts at companies that use slack can use Detections and Hunting Queries to monitor Slack activity.
How we built it
Log Agent is built using Python. Azure Sentinel is used for Detections and Hunting Queries.
Challenges we ran into
Building the log agent using Slack API was challenging since not all APIs are available for free tier. Since this was our first cybersecurity project, it was initially difficult to visualize our product.
Accomplishments that we are proud of
We were able to use Azure Sentinel to show that it can be used to monitor even products that are not created by Microsoft.
What we learnt
Learning about all the features of Azure Sentinel made me more interested to explore the field of CyberSecurity.
Steps to Secure Slack with Azure Sentinel:
Step 1
: Create a Slack API token for log collection. Refer to our Github Repository's Readme file for detailed steps.
Step 2
: Create
Azure Sentinel WorkSpace
and get the credentials(AZURE_LOG_ANALYTICS_WORKSPACE_ID and AZURE_CLIENT_AUTHENTICATION_KEY).
Step 3
: Clone repository
'SecureSlackWithAzureSentinel'
using the following git command:
git clone https://github.com/msvdpriya/SecureSlackWithAzureSentinel.git
Step 4
: Configure Credentials that you got in Step 1 and Step 2 in the setup.py file of the Log agent. Edit the following variables in the file and set the credentials as their values:
SLACK_API_TOKEN
AZURE_LOG_ANALYTICS_WORKSPACE_ID
AZURE_CLIENT_AUTHENTICATION_KEY
Step 5
: Run setup.py (This step will setup
Log Agent
)
NOTE: python and pip3 are prerequisites to run the setup.py file. All other requirements will be downloaded when you run setup.py file.
This step will also configure crontab in your machine that will run the app.py script(Log Agent) periodically to fetch logs from Slack API and upload it to
Azure Sentinel Log Analytics workspace
. On Windows machine, you can run setup the file 'setup.py' as a scheduled task.
Step 6
: Verify that the logs are being pushed to
Azure Sentinel Log Analytics Workspace
.
Step 7
. Use the KQL queries that are present in detections and hunting folders of the project to detect and hunt for cybersecurity threats on
Azure Sentinel
.
Built With
azure
azure-log-analytics
azure-sentinel
python
slack-api
Try it out
github.com | Protect Slack with Azure Sentinel | "Protect Slack with Azure Sentinel" is an end-to-end solution to Secure and Monitor Slack using Azure Sentinel | ['Priyadarshini Murugan', 'Sumanth Muni'] | ['Honorable Mention'] | ['azure', 'azure-log-analytics', 'azure-sentinel', 'python', 'slack-api'] | 3 |
9,917 | https://devpost.com/software/olaf-dlp-open-source-data-loss-and-liability-protection | OLAF data ingested into Azure Sentinel
Inspiration
The recent Waymo-Uber lawsuit and the continuous almost-daily stream of news stories on large-scale data breaches and leaks has highlighted the necessity of auditing and protecting the information that flows both into and out of an organizations networks and computers. Both data exfiltration and infiltration can make organizations liable for lawsuits and criminal charges over intellectual property theft or confidential data disclosure. Protecting information like blueprints or engineering drawings or source code or sensitive financial or health data that may reside in files that users can download or take home with them on a USB drive are now essential parts of any organization-wide security plan.
Data Loss Prevention (DLP) systems are now offered by most large enterprise security vendors and cloud services providers like Google and Microsoft. But most DLP solutions available today are commercial proprietary systems that are closed-source and require centralized user and device management like Active Directory. In addition to the considerable initial costs such systems will incur, a closed-source security solution does not allow its code to be audited or tested to find potential bugs or security vulnerabilities or insecure methods of storing data. A security hole or data breach in an enterprise-wise DLP system could be disastrous for an organization.
What it does
OLAF (
O
nline
A
utomated
F
orensics) is an
open-source
digital forensics tool for public-facing PCs or business desktops or other endpoints, that can classify and audit in near real-time documents and images users downloads or copy to removable storage. OLAF continuosly monitors a PC for activity like downloading or mounting external storage, then extracts the text or image content of files transferred using open-source libraries. Content analysis is then performed on the artifact using different methods inlcuding analysis of images by ML services like Azure Cognitive Services Vision. This information as well as metadata like the date and time a document was downloaded or copied and the user and machine name where the operation occured is logged to Azure Sentinel where it provides a permanent event log of data movement of potential intellectual property or sensitive or PII data, which can then provide evidence of a breach of an organization's policies on information protection.
OLAF helps an organization determine how information flows into and out of their systems when users download files using their web browser or copy files to USB and other removal storage devices and can help enforce policies on using and transferring intellectual property, trade secrets, PII or other sensitive and confidential information. It can also detect when sexual or other inappropriate content from the Internet enters into an organization's systems which may violate computer use policies. OLAF is a open-source standalone program designed to be modular and extendable and can log to any available log target from simple text files to cloud-based SIEM services like Azure Sentinel, without locking an organization into any particular user management or log collection technology.
I have written previously about the image classification capabilities of OLAF in a Code Project
article
which I entered into their
Image Classification Challenge
contest last year and won 2nd place. For this hackathon I added the following capabilities to OLAF:
Detect storage volumes mounted and unmounted in Windows and monitor the files transferred to them.
Use Apache Tika for cracking and analyzing the content of files downloaded or copied to removable storage.
Use dictionaries and regular expressions to detect when a file may contain PII or confidential or sensitive information like a competitor's intellectual property.
Add metadata like file hashes and the current Windows application that has the user's focus when files are created or copied.
Log file analysis results and metadata to Azure Log Monitor and create queries in Azure Sentinel to surface potential data-loss events from the OLAF log data.
How I built it
Design
OLAF is a .NET Framework app written in C# targeting Windows desktops. Although some platform-specific detectors use functions from the Windows API, the base OLAF libraries are cross-platform and should run on .NET Core, or on Mono for Linux or Mac. OLAF currently runs as a console app for development but can easily be converted to a Windows service for production use.
OLAF is designed around a multi-threaded message queue where the different components can listen to and respond to messages without blocking execution of other components. Since OLAF is designed to run continously as a background service, performance without affecting the responsiveness of other user applications that are running is a key factor in the design.
Modularity and extendability are also key factors in the design. OLAF components are designed to be plugged in and out without difficulty with each category of component deriving from a common base class. There are 3 main classes of components:
ActivityDetector
,
Monitor
, and
Service
:
Activity detectors
are lightweight components designed to receive notifications from the operating system and then place messages on the OLAF queue notifying of file or other activity that OLAF components are interested in. Activity Detectors do not do any significant processing on their own and are only there to quickly send messages to monitor components when for instance the user plugs in or removes a USB drive. Activity Detectors must be able to handle a large number of notifications coming in from the operating system and place activity messages on the queue where
Monitor
components process them serially.
Monitors
are the components which handle activity detection messages and identify the image and document artifacts that will be preserved and analyzed by OLAF. For instance the
DirectoryChanges
monitor receives file system activity messages about new files being created at a particular storage location and first copies the file to a internal data folder to preserve it before reading the file and creating a
FileArtifact
message that will be processed by a
Service
.
Services
process file and image artifacts and implement file cracking, text and metadata extraction, image and text analysis, classification, PII detection, and event log storage. A service will process an
Artifact
, enrich it with additional information and metadata and then place it back on the queue where it is available for processing by other services. For instance the
Tesseract OCR
service will extract text from an
ImageArtifact
and create a
TextArtifact
which is placed on the queue and can be processed by a text
Classifier
service and finally a
Storage
service which stores the artifact and metadata as a log entry in Azure Log Monitor. Service components can be further broken down into
Extractor
,
Classifier
and
Storage
components.
OLAF is designed so that developers can quickly assemble a pipeline of services to process artifacts. A
Pipeline
object is a set of OLAF services that process an artifact in sequential fashion e.g. the
Document
pipeline which is used for DLP
Libraries and Services
OLAF makes use of several open-source libraries as well as SDKs for Azure machine learning services:
Extractors
Name
Description
Tesseract
Open-source
OCR engine
which can extract text from images. OLAF uses a wrapper called tesseractdotnet which also includes a .NET wrapper for the
leptonica
image processing library.
Apache Tika
Open-source
document processing library
that can extract full text and metadata from many common document file types like
.PDF
,
.DOC
and
.XLS
Classifiers
Name
Description
Accord.NET
Open-source .NET
machine learning library
which contains implementations of many algorithms like the Viola-Jones object detection framework which can detect if an image contains human faces.
Azure Computer Vision
Azure's ML-powered
image analysis
service which provides powerful classification and recognition capabilities. For images that users download or copy, Azure Computer Vision can classify images using categories, captions, and tags, and can also determine if an image contains racy or sexual content.
Azure Text Analytics
Azure's ML-powered
text- analytics
service. Recognizes and extract entities like people or place names from free text.
In the near future I also want to try out Google's
Cloud DLP service
which has both a free tier and official .NET client for text analysis and classification
Storage
Name
Description
Azure Blob Storage
Azure's bulk
storage service
which can store both structured and unstructured data. OLAF's
AzureBlobStorage
component
can store both text and image artifacts for preservation.
Azure Log Analytics
I used Tobias Zimmergen's Log Analytics
wrapper
from his terrfic
article
on using the
Log Analytics
Data Collector API to create custom tables and event types. OLAF creates a log entry for every document and image artifact it analyzes.
Challenges I ran into
When OLAF detects a storage volume is added to the system it spawns a
DirectoryMonitor
to monitor files written to the volume. However if you attempt to remove the volume using the Windows tray icon program then Windows will complain that the drive is still in use...because OLAF has a monitor running on it :o I've started
the code
to register and process the Win32 messages but it isn't all hooked up yet so for now to remove a USB drive when OLAF is running you'll have to just to yank it out the old-fashioned way.
Accomplishments that I'm proud of
I haven't been able to find an open-source DLP solution except for MyDLP which seems to have been discontinued. OLAF DLP is an end-to-end open-source DLP that is both free and capable when combined with Azure Sentinel and I hope to continue development on it.
What I learned
Computer security is always an opportunity to learn many new things and developing OLAP I learnt everything from Windows API calls to working with a SIEM.
What's next for OLAF DLP: Data loss protection using ML and Azure Sentinel
Adding Google Cloud DLP support.
Built With
.net
azure
azure-sentinel
image-classification
machine-learning
Try it out
github.com
www.youtube.com | Data loss/liability protection using ML and Azure Sentinel | Automatically analyze documents users download or copy to removable storage to detect violations of organization policies regarding intellectual property, trade secrets, and sensitive data. | ['Allister Beharry'] | [] | ['.net', 'azure', 'azure-sentinel', 'image-classification', 'machine-learning'] | 4 |
9,917 | https://devpost.com/software/ip-addresses-logon-suspect | Inspiration
I will flow the steps in the blog that is my first cybersecurity solutions
https://techcommunity.microsoft.com/t5/azure-sentinel/creating-digital-tripwires-with-custom-threat-intelligence-feeds/ba-p/1320981
What it does
Creating digital tripwires with custom threat intelligence feeds for Azure Sentinel
How I built it
Azure Sentinel Azure Storage
Challenges I ran into
first cybersecurity solutions
Accomplishments that I'm proud of
keep learning
What I learned
Threat hunting
What's next for IP addresses logon suspect
it was just practiced in Microsoft solution
Built With
azure
sentinel | IP addresses logon suspect | Creating digital tripwires with custom threat intelligence feeds for Azure Sentinel I will flow the steps in the blog that is my first cybersecurity solutions | ['Abdelrazek Rizk'] | [] | ['azure', 'sentinel'] | 5 |
9,917 | https://devpost.com/software/self-installing-hardened-linux-cefsyslog-collector-appliance | Simple install process example
Inspiration
I've been working with SIEMs for more than 10 years and I had this idea quite some years ago to do a quick self-installing syslog collector appliance much like enterprise SIEM vendors do, but more simpler and hardened. The idea was to provide a simple self-installable platform that can be used standalone, or for an MSSP to control and be a "blackbox" for the customer.
What it does
Create a self-installable ISO file that when booted in a system it will automatically install a Centos 7 based system that will be hardened, and will install the Microsoft CEF Agent (MMA Agent + rsyslog conf) configured and set up against the workspace of the user choice. From boot to the system appearing in the Azure Portal and receiving CEF logs happens in less than 3 minutes.
How I built it
As simple and elegant as possible, using 90%-ish bash and a little bit of python to handle SHA512 salted passwords.
Challenges I ran into
Too many variables and scenarios, which meant too many try-and-error.
Accomplishments that I'm proud of
This is something like the licensed and paid enterprise collectors, but free in a closed appliance format that is easy and quick to install. As far as I know and searched there is no thing like this. it also allows a template system to make other types of systems.
What I learned
A lot more advanced sed's regex, how to circumvent bash's limitations, how the anaconda system installer works behind the scenes.
What's next for Self-installing hardened linux CEFsyslog collector appliance
Expand the azure sentinel template to automatically create and upload custom workbooks through the API, and maybe create an ARM template for this. Expand the template functionalities of the program. Do a penetration testing scenario and harden the appliance even more.
Built With
bash
centos
python
Try it out
github.com | Self-installing hardened linux CEFsyslog collector appliance | A simple program that will create a Centos7/RHEL7 CIS hardened system and will do everything automatically from creating the ISO to installing the system and connecting it to the Azure workspace. | ['Cristian Ares'] | [] | ['bash', 'centos', 'python'] | 6 |
9,917 | https://devpost.com/software/identity-investigator-for-security-analysts | Sherlock User Investigator Workbook Overview
Inspiration
Necessity is the mother of invention.
Threat hunting and investigation requires a point of pivot and a view that encompasses situational awareness around that pivot. This provides analysts with the critical context to analyse an incident scenario across a timeline and all security controls.
There are mainly 3 central pivots, user, ip, host machine. We could not find a way in Sentinel to have that pivot based on a user during our investigations so we decided to build it. The user pivot is extremely useful in identifying the cases of account theft/infiltration/admin compromise/initial entry. Currently within the Sentinel investigation panel you can only pivot on a user with scope limited to sentinel alerts and details limited to very basic information. Any further details on the user pivot can only be seen as a query output which is not visually insightful.
What it does
This product provides a workbook to quickly investigate user activity across all security tools feeding into sentinel and contextualize the investigation to aid the new pivot point. It utilises the strength of workbook visualisations to create a view that an analyst can interpret easily and succinctly.
How I built it
In order to demonstrate the benefits an array of applicable sources were utilised e.g proxy, cloud app, signin, office activity etc.
We onboarded custom log sources such as ZScalar as well Microsoft security technologies and then created KQL queries with custom extractions to build the workbook panels. The logs from these various security controls are typically analysed when ascertaining the scope of an attack via a compromised account. The various log sources have different requirements to satisfy the condition of identifying the account associated to an activity.
Normalisation is still a largely unsatisfied feature within Sentinel.
KQL and REGEX is used for the differing extraction of the user account details in the various sources.
The panels – each addressing a different source - within the workbook, are used to bring all the data for that user in one view.
Supporting platforms are also linked within the workbook to support the analyst’s view of that user e.g AAD user profile.
Some data sources such as O365 Security Alerts would not consistently have user account details in all events.
Challenges I ran into
No existing way to deep link a workbook from the incident to auto-fill the input values and many time the extractions had to be done in KQL.
Not all alerts have user account details within the logs so these type of alerts cannot be connected into the user view.
Different sources store different user data e.g username vs email vs first and last name (johnd1,
john.doe@x.com
, john doe). To link these all to the same user - AAD data needs to be used and pulled into Sentinel, stored in a table that can be referenced.
Accomplishments that I'm proud of
The workbook has been very useful in real world scenarios already and has aided our analysts to perform their investigations faster.
The workbook is very directed, it manages to provide great context without being noisy, and gives much better guidance for a hunt. It also provides much better situational awareness to guide decision making in terms of what hunt avenues to pursue.
What I learned
Extraction from json and string fields.
The flexibility of KQL, KQL querying.
Interactive workbook creation, e.g showing a panel based on parameter conditions.
The various strengths of workbook parameters.
How to create graphs, interactive tiles, tabs, maps, clickable grids. These features available within workbooks being fully realised to facilitate effective and useful data analysis.
What's next for Sherlock User Investigator
We would like to expand Sherlock to show a comparison for the user against the rest of the organization or their peer group which can be used as a trigger. Furthermore add the ability to trigger playbooks from within the workbook via custom actions. Additionally, we plan to make this longer term a “one hunt to rule them all” workbook by including in-built queries and pivots for Machines, IP addresses and IOCs (e.g. Hashes, filenames, processes).
Built With
azure
json
kql
regex
sentinel
sentinel-monitoring
workbooks | Sherlock User Investigator | Get complete visibility into a user's activities to accelerate threat investigation/hunting | ['Herah Khan', 'Matthew Ladewig', 'Himanshu Anand', 'paul moran'] | [] | ['azure', 'json', 'kql', 'regex', 'sentinel', 'sentinel-monitoring', 'workbooks'] | 7 |
9,917 | https://devpost.com/software/sentinel-honeypot-reporting | Windows summary.
Cowrie summary.
Cowrie authentication charts.
Process create events (filtered).
IIS request data.
Windows authentication chart.
Cowrie session data.
Windows user activity.
DNS requests (filtered).
Inspiration
For the past several years I have operated a variety of deception operations, including several flavours of honeypot. I've always struggled with being able to find an off-the-shelf solution that meets my analytic requirements, or have found
potential
solutions having flaws that - over time - deemed them impractical.
During the NZ lockdown I was faced an opportunity to learn more about Azure Sentinel to meet growing customer demand for it, so I began my learnings by onboarding several hosts to my Sentinel instance where I'd set up the parser, workbooks and analytics rules from the
Sentinel ATT&CK
project. It was this project that very quickly inspired me to migrate my honeypots from a basic ELK stack to Sentinel.
What it does
The solution consists of two main components:
Windows honeypot workbook:
this ingests Windows security, IIS and sysmon logs to report on authentication, user and system events.
Linux honeypot workbook:
this ingests JSON logs from the Cowrie SSH+telnet honeypot and access logs from a Dockerised Apache server via custom parsers to report on authentication, user, system and web activity.
Key data points can be further analysed via parameters in the workbook, meaning analysts don't need to jump between several workbooks to make multiple queries to answer questions.
Build documentation accompanies both workbooks to ensure that honeypots are set up and managed in a safe manner, so not to expose their operator to any undue risk.
How I built it
Workbooks:
I began by listing the insights I wanted to make (e.g. geographic trends, new RDP and web exploits) and what data that would serve as valuable intelligence. Based on this I determined what event types had to be collected, what the relationships between event types were and what workflow could be developed. For example: a successful authentication involves an account signing on and therefore that account name is a parameter that can be used to filter sysmon events.
Parser:
Once I discovered how to ingest the Cowrie JSON log I generated a spectrum of events by interacting with the honeypot. I gathered one of each event type and mapped out their key values, resulting in a list of required event definitions. I certainly ran into some challenges with this one that I'll describe below.
Challenges I ran into
I faced two main challenges:
Escaping backslashes in usernames so they can be passed as a value from multi-select dropdowns. While a single value can be easily escaped in the destination query by defining it as a literal (i.e. preceding it with an @ symbol), when multiple values are passed the query is broken if the username is of the format username\domain. This was resolved by escaping the names in the dropdown (as seen in
this commit
).
I wasn't aware that the OMS agent could be configured to tail any log on a system, so spent several hours writing regex to form a parser for Cowrie syslog output. After struggling to consistently parse the logs I turned to Microsoft documentation and learned of the custom log, making parsing much, much easier by allowing me to tail the Cowrie JSON log.
Accomplishments that I'm proud of
I'm very proud that I've achieved what I set out to do in such a short space of time (~1 month), and am yet to encounter something that I've wanted to do that I can't be done. Honeypot reporting is potentially something that Microsoft didn't specifically have in mind when Sentinel was conceived, and I definitely believe this speaks to the flexibility and capability of Azure Sentinel.
What I learned
Prior to this project I had a very loose understanding of how the various components of Sentinel can work together to help develop extremely efficient analyst workflows. Now I have far more confidence to speak to the capability of Sentinel and support this with experience.
What's next for Sentinel Honeypot Reporting
Like most of my projects, both honeypot workbooks will be continually developed. Next I plan to develop accompanying analytics rules and Logic Apps to automatically push custom indicators to:
MISP.
Firewall and Defender ATP blocklists.
Built With
azure-sentinel
cowrie
sysmon
Try it out
github.com | Sentinel Honeypot Reporting | Honeypot reporting tends to be 1-dimensional. By leveraging Sentinel, researchers can display and interact with sensor data in ways that provide much deeper insight into attacker behaviour. | ['Chris Campbell'] | [] | ['azure-sentinel', 'cowrie', 'sysmon'] | 8 |
9,917 | https://devpost.com/software/customer-incident-report-solution | This is our user-facing front end, a Microsoft Form that will allow users to self-report suspicious activity.
Form submissions are fed into a logic app that will direct the data to Log Analytics.
A function was written in KQL to translate raw data from form submissions into readable metrics.
An analytic rule will create incident tickets when a user describes their experience as having a High or Critical level of severity.
A workbook was designed to query submission information from the last thirty days and display it in a graphic format.
The workbook can be configured to display information graphically to provide administrators with an easy-to-read front end.
Inspiration
Working within the military, our developers have experienced IT obstacles and deficiencies from first hand experience in the user process. Whenever large enterprise environments are implemented, the end user becomes obfuscated; we hope to eliminate that disconnection through the use of Microsoft Forms and Azure. Our team within the
Microsoft Software and Systems Academy
have created a self-reporting system for end users in an Azure environment.
What it does
When an end user feels there is something not quite right with their Information Security experience, they can self-report and request response from a team that is listening to their feedback. This data is fed into Azure Sentinel to create incident tickets and display statistics for administrator review.
How we built it
Before
Azure Sentinel
, our first task was to create a
Microsoft Form
wherein users could detail their concerns and experiences to include requesting contact with the information security team. This organizationally available Form will then feed responses into our Azure Sentinel analytics space to include a tracking system and Workbook for critical incidents and response requests for individual users.
Challenges we ran into
Creating workbooks and logic apps are sometimes restricted to organizational accounts. This restriction may prohibit outside users from implementing the solution.
Accomplishments that we're proud of
I am proud of my teammates endeavoring to put forth their individual competencies to learn more about Incident Creation Rules, KQL Queries, and Workbook creation. We decided that incidents should be created based on certain criteria from our responses, and created an incident query line based on
analytic rules
.
What We learned
KQL is a language that we learned together in order streamline our solution; after multiple conferences to create a more readable environment for our solution platform, we were finally able to navigate the language with fluency.
What's next for our Customer Incident Report Solution
Our next step is to create a domain environment to test individual user response against assignment of incident tickets.
Built With
kql
log-analytics
logic-apps
workbooks
Try it out
forms.microsoft.com | User Incident Report Solution | Provide enterprise users within an Azure environment a self-reporting solution for suspicious activity. | ['Levi Nordine', 'Christopher Caldwell', 'Keenan Williams'] | [] | ['kql', 'log-analytics', 'logic-apps', 'workbooks'] | 9 |
9,917 | https://devpost.com/software/azure-sentinel-huginn-dataconnector | Huginn
This is a Function App that will listen to webhooks from
Huginn
and bring them into Azure Sentinel. Huginn is a system for building agents that perform automated tasks online, and is especially good at scraping information from disparate sources, such as FTP, IMAP, Jabber, MQTT, RSS feeds, Slack, websites, and much more. Huginn's Agents create and consume events, propagating them along a directed graph. A Post Agent can be used to send webhooks to receivers, such as this Function App.
Built With
azure
function-app
github
Try it out
github.com | Azure Sentinel Huginn DataConnector | This is a Function App that will listen to webhooks from Huginn and bring them into Azure Sentinel. | ['Andrew Cantino'] | [] | ['azure', 'function-app', 'github'] | 10 |
9,917 | https://devpost.com/software/cyberhack | Inspiration
The rate at which people are been attacked wrongly on social media platforms and other platforms which could lead to suscidal attempt inspired me to curb such act.
What it does
It quickly checks or go through anything that wants to be posted on social media by an end user and prevent the user from uploading any form of bully content through text, voice notes, pictures or videos
How I built it
I made use of a social media content on twitter as my training set so I identified copus that is words or common languages that don't attribute to a bully I then categorize a bully and a non bully so when my model Identifys a bully it prompts me.
Challenges I ran into
One challenge was trying to clean and organise my data to get good result and trying to deploy
Accomplishments that I'm proud of
I was finally able to get the intended result of my project
What I learned
The best way to work with text datasets to get good results
What's next for Cyberhack
I want to still make it identify vioce note, videos or pictures that may still be a bully so I can deploy in many socail media platforms to reduce the rate of bully and passing wrong news accross
Built With
python
Try it out
github.com | Cyberhack | Its a model that detects fake news and bully online. | ['Ugochukwu Nnachor'] | [] | ['python'] | 11 |
9,921 | https://devpost.com/software/sterilization-gun | Inspiration
I am mechanical engineering specialized in vibrations. While watching how the recent pandemic of coronavirus disease-19 (COVID-19) is causing a lot of deaths worldwide and it led to lockdown in most of the countries and economic damage. I have gathered a team to apply simple concepts hoping it will affect our world war against this pathogen.
What it does
We have recalled a basic phenomenon that Anybody – which is consisted of some certain substances – has a definitive physical attribute which can be defined by the term of The Natural Frequency of this body. If this body – in a way or another – is subjected to a generated frequency which is equal to its Natural Frequency, it collapses. This phenomenon is called the Resonance Effect. On the basis of this scientific fact, So, Each pathogen including viruses has it’s own resonant frequency and upon exposure to this frequency, the virus will be destructed by mechanical stress. The idea is to present a Mobile Application that is connected to a means that is able to generate the needed frequency that shall be equal to the Natural Frequency of a certain noxious pathogen and as a result, this pathogen collapses and the surrounding environment satisfies its needed level of Sterilization. The challenge was to know the range of frequencies needed, but literature was sufficient to predict the range of frequencies that we can use at the start to be tested
How we built it
It consists of two main parts: The Mobile Application and The Gun. The Mobile Application is built using Javascript and React Native Cross-Platform. The Gun is built using three main parts: a Wireless Receiver, a Frequency Generator, and an Ultrasonic Transducer. There are two configurations of the Gun: The first has A Raspberry Pi board (as a Wireless Receiver and a host for needed Software), a USB Function Generator (as a Frequency Generator) and an Ultrasonic Transducer where the SmartPhone communicates with the Raspberry Pi in a wireless way (Wi-Fi or Bluetooth) and the Raspberry Pi – which contains the needed software for the Function Generator – commands the Function Generator to generate a Sine Wave with the needed frequency which is transformed by the Ultrasonic Transducer to Sound/Ultrasonic waves needed to collapse the intended pathogen but, the second has A Bluetooth Module (as a Wireless Receiver), a Microcontroller Board (as a Frequency Generator) and an Ultrasonic Transducer where the SmartPhone communicates with the Microcontroller in a wireless way (Bluetooth) through the Bluetooth Module by certain commands which are interpreted by the microcontroller to generate a Sine Wave with the needed frequency which is transformed by the Ultrasonic Transducer to Sound/Ultrasonic waves needed to collapse the intended pathogen.
Challenges we ran into
The first challenge we had, is that the idea was to create the needed Ultrasonic waves using only the Smartphone but, it was faced by the limitation that the frequencies generated by the Smart Phone are limited by only 25 kHz and we need more than 300 kHz so, we have thought about an additional means to our Mobile Application to achieve the needed frequencies.
And secondly, for the Hardware part (The Gun), we had run into the challenge of the trade-off between the quality of the generated waves and the cost of the used hardware so, we have presented two solutions. At first, the quality of the generated waves is great but the hardware cost is higher. In the second one, we have concentrated our efforts to achieve a cheaper solution with acceptable quality which has been achieved.
Thirdly, Generating a sample tone from the IOS platform had been a challenging thing!
Accomplishments that we're proud of
We are proud of overcoming the limitation of The Smart Phone to generate the needed frequencies. Also, we have to be proud of presenting solutions that are much cheaper in comparison with other presented concepts or pre-existed solutions.
What we learned
We have learned a lot about many researchers that have taken the same path with similar viruses. They have achieved success in fighting those viruses. We have learned from them the technique to measure the frequency and the technique to create the frequency to fight it.
What's next for Sterilization Gun
Based on this information we can use the previously recorded frequencies which are effective in
killing viruses similar to the COVID-19 virus to predict the frequency which is needed to kill it
which is mostly in range kHz. Or we can predict the frequency through building an algorism
based on the size and equivalent frequencies of previously recorded viruses. Further studies
will be needed to test these frequencies experimentally.
We offer an affordable, easy portable user-friendly and programmable mobile application that will
help in emitting High-frequency ultrasound waves to destroy the viruses.
Built With
custom-ui-kit
hc-05
i.mx
javascript
raspberry-pi
react-native
react-native-bottom-sheet
react-native-lottie
react-native-tone
stm32
Try it out
drive.google.com
github.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com | Sterilization Gun | Creating a high-performance mobile application that connects wireless to a portable device, that generates up to 1 MHz to achieve resonance frequency and sterilize a closed area containing the device. | ['Ashraf Talaat Hussien', 'Mohamed kassim', 'Hassan El Shenawy', 'Nehal Ibrahim Ghoneim'] | [] | ['custom-ui-kit', 'hc-05', 'i.mx', 'javascript', 'raspberry-pi', 'react-native', 'react-native-bottom-sheet', 'react-native-lottie', 'react-native-tone', 'stm32'] | 0 |
9,921 | https://devpost.com/software/quaranti-virus | Inspiration!
While the lock down is mostly successful to stop the spread of the corona virus, some people just wanna be rebels.
Our goal is to help the government do it's job easier and faster so we go back to our normal life as soon as possible.
it's getting lonely out here, i miss my friend.
What it does?
Our plan is to give a wristband to the patient to wear it for 14 days, tracking location, and some symptoms of Covid-19, which will be updated in the mobile application of the patient and the website of the authorities.
How we built it ?
We used our already acquired knowledge in Android Studio to create a suitable environment for the quarantined people. The app isn't restricted to the reading of the sensors provided by the gadget, but also take it to analyze the data and provide other manners of help to diagnose their medical condition.
Challenges we ran into ?
The biggest challenge in creating this app proved to be the distance between our team members, since the online working experience is still entirely new, which poses difficulty concerning synchronization between members and organization of the different parts of the project. The coding part is already hard enough as well since we are mostly self-learning Java and Android SDK, but our current proficiency in other languages makes the learning curve more gentle.
Accomplishments that we're proud of !
I'm proud i've improved my infos about the current covid-19 situation, as well as coding skills, and general knowledge about sensors. We are so excited we might get a chance to reduce the pandemic effect and help our countries.
What we learned ?
In these brief 3 days, life was only about this project. 14 hours at least for each team member everyday. Constantly working to develop our project as good as we can in those days. My skills with java and android studio skyrocketed. I have even re-studied my logic circuit courses and electronics to have a better understanding of what i'm doing. And whether we win or not, i'm proud of the work we did.
What is next ?
For the future we want to develop the project to finalize it, and communicating with multiple authorities in different countries to adopt the project and a team to build the wristbands, since we're all electrical engineers student we can help. We're going to design a website for the authorities to control and use.
Built With
android-studio
html5
java
xml
Try it out
github.com | QuarAnti-Virus | Our plan is to build a wristband to control the spread and damage caused by corona virus. The wrist is accompanied by an app. | ['elie abi char', 'Elias Bashalany', 'Elie Karam', 'Cybele Ghanem'] | [] | ['android-studio', 'html5', 'java', 'xml'] | 1 |
9,921 | https://devpost.com/software/covidscan-mly983 | Inspiration
Our inspiration was research studies published about the Covid-19 pandemic. The rate of transmission of the Covid-19 virus depends on how quickly we can diagnose and test patients, and our current method of testing can take days for results. While patients wait for results, they could have already spread the disease to other patients, doctors or people in their community.
We wanted to create a faster method of detection that could be performed by anyone, not just a doctor or test facility. This way, we can easily get infected patients the assistance they need without having to wait, as every minute we waste could mean a live lost.
We decided to put our machine learning skills to use and build an application where anyone could use a CT scan to determine if a patient has Covid-19, Pneumonia (very similar disease) or no disease at all. This method of detection would allow for easy diagnosis in a timely manner.
What it does
It's very simple; the user takes a picture of a CT Scan, and our Image Classification ML model classifies if the image shows no disease, Covid-19, Bacterial Pneumonia or Viral Pneumonia. Then, the user can read more information about the disease and add a patient to the management system, including general information, images and notes that could be handy.
How we built it
Our app is built around 2 of Apple's new machine learning frameworks; coreML and createML. We used these over Tensorflow due to our experience with these frameworks and the easier implementation within Swift and X-code. We built a realtime camera screen using AVCam, and then added our machine learning model to perform realtime detection. We added a prediction label as well, where our model outputs what its prediction is and how certain it is in its prediction.
We also used SnapKit and data structures in Swift to build a patient management system, where a doctor can input key information about their patient, such as their demographics, condition and an image of their CT scan for easy recall and analysis.
Our user interface was built entirely using UIKit and TableView, as we wanted to make the GUI easy to use and pleasant for the eyes. UIKit is the standard UI framework for iOS, and TableView allowed us to make easy tables for our management database.
Challenges we ran into
Our main challenge was implementing the machine learning model, as it required tons of images and data which was hard to locate. After hours of searching, we located datasets that could be used to train the model. The model training was also slow due to the large volume of images and we had to wait all night for it to process and produce a coherent model which we could use.
We also had some minor challenges with TableView and implementing our patient system, as storing an image and then recalling it was not something we were familiar with and took some time to learn. However, once we figured it out it was pretty straightforward and easy to understand.
Accomplishments that we're proud of
We're proud of our machine learning model since we needed it to be very accurate since it would be used in hospitals. Finding a lot of images and classifying them was a daunting task, but it was well worth the effort as it made our model more accurate and better at diagnosis.
We are also very proud of our UI, as we wanted to make design a priority and we can safely say that we were able to do that. We were not very familiar with TableView, so implementing TableView for our patient system was also something new and fun to experience.
What we learned
We learnt a lot about design and proper data storage in Swift. We usually treat our UI as an afterthought, but putting it as a real priority helped us learn something new and unique about the struggles and challenged that we face when it comes to design. It was frustrating when our image was just off center, and fixing those things showed us the trouble designers have to go through and it just grew our respect for them immensely. We also finally understood how to store information in Swift using Arrays and Dictionaries, and how useful such data structures can be for complicated systems.
We also grasped how much of a difference high resolution images can make; the more the data in an image, the better our model was able to train and understand, which was a new discovery for the both of us. While it seems obvious, we never strived for high resolution images but this changed after this project.
What's next for CovidScan:
We definitely want to add more diseases that can be recognized by our model, and not to limit the number of diseases so we can expand past just the Covid-19 pandemic. We also hope to keep training our model as more data is published, as this would allow for more accurate diagnosis which is extremely important when dealing with a patient's health.
Built With
coreml
createml
ios
machine-learning
snapkit
swift
uikit
Try it out
github.com | CovidScan | CovidScan is a machine learning based application that allows doctors to quickly determine if patients have Covid-19 or Pneumonia based on CT scans. | ['Anish Kataria', 'Krish Malik'] | [] | ['coreml', 'createml', 'ios', 'machine-learning', 'snapkit', 'swift', 'uikit'] | 2 |
9,921 | https://devpost.com/software/tidal-predictions-kxrijb | Inspiration
"Britons warned to prepare for power blackouts in coronavirus lockdown" is a headline we came across recently.
Upon reading the article that followed, we realised that the electricity demand is at its peak due to people being at homes all day and the approaching summer. As our team's interest lies in renewable energy systems, we thought of an idea to maximise power generation from existing systems such as tidal lagoons.
What it does
A tidal lagoon has key components such as a sluice gate (to allow for water to enter), a turbine and a generator. Currently, predicted tidal heights are far from what what they are observed on the day.
The total observed height on any given day is a sum of the predicted tide and a residual term, also called a surge tide. This residual term is a value that is brought about due to weather changes, winds, the moon's position etc. and is hard to predict. However, this term causes a change in observed water levels and leads to loss in power (value in terms of Mega Watts) that could have been generated.
To solve this, at a time when power output is needed the most due to lockdown, we attempt at predicting the total observed height by trying to predict the residual term. Essentially, this would help generate more power than is currently able.
We have used Machine learning to solve this problem.
Our predictor predicts the total observed height on the day with 93.59% accuracy, hence maximising power output.
How we built it
We built it using python.
A 7 step process was used.
1) Data collection: We downloaded this dataset from the British Oceanographic Data Centre website for a site named "Newport". The data contains values from 2015-2019 at 15-minute intervals.
2) Data preparation and visualization: Performed by cleaning the data and creating probability density plots and pairplots.
3) Model Selection: Upon evaluation, random forest turned out to be the best combination of accurate and fast.
4) Model Training: Did a 80:20 Train:test split and trained our random forest model on the training data. Then used this model to predict values based on test data inputs.
5) Evaluation: Compared the accuracy of the predicted values to the actual values.
6) Parameter tuning: Tuned parameters such as "n_Estimators" which is the number of decision trees the model would use. Found an optimum number to be 128.
7) Accuracy: Accuracy is 93.59% and Mean Absolute Error (MAE) is only 0.23 degrees.
Challenges we ran into
Certain challenges we ran into included collecting and preparing the dataset. Alongside, figuring out the correct model took time and effort as each model would take minutes to run.
Accomplishments that we're proud of
We are proud that we were able to increase the accuracy of our model from 42% to 93.59%.
What we learned
We learned and applied lots of Machine learning!
What's next for Tidal Predictions
Looking at fine-tuning parameters to further increase accuracy and make the program run quicker. We also wish to develop an app/website that could provide a close-to-actual prediction for anybody who is seeking to know tidal heights eg. fishermen.
Built With
python
Try it out
github.com | Tidal Predictions | Maximising energy harvest in a time where electricity usage is at peak due to lockdown. | ['Arushi Madan', 'Rohan Chacko', 'Arun Venugopal'] | [] | ['python'] | 3 |
9,921 | https://devpost.com/software/covid-tracer-0wv6j5 | Full report
link
Challenges we ran into
Making the database connect to a webserver was a major issue as it was difficult link Django and authenticate the user. Most of the user specific applciations are not yet restricted so most people can access them all.
What's next for Covid Tracer
Fully developing the server interface.
Rolling out the application among the userbase as it is dependant on being used by the comunities. There would be a need for mass advertising and making locals aware as most people have mobile phones.
Built With
android
django
firebase
python
Try it out
github.com
drive.google.com | Covid Tracer | A way to track down and current people that have and may have contracted Covid-19. | ['Humphrey Chiramba', 'Tonderai Saidi', 'Sindiso Mkhatshwa', 'Shingirai Maburutse'] | [] | ['android', 'django', 'firebase', 'python'] | 4 |
9,921 | https://devpost.com/software/covid-19-8elv7b | Inspiration
DEpressed people
What it does
help them survive by giving them tips
How we built it
using android-studio
Challenges we ran into
making a video,in a perfect way
Accomplishments that we're proud of
It is our first hackathon,and we are not experts in coding
What we learned
Time management and how to be great team members
What's next for COVID-19
launch our app,and get more code to it
Built With
android-studio
Try it out
drive.google.com
github.com | COVID-19 | An application that help people overcome the dificulty of this quarantine | ['Zaynab Atwi', 'Hassan Nehme'] | [] | ['android-studio'] | 5 |
9,921 | https://devpost.com/software/job-flow | Inspiration : Seeing most the population go from employees to freelancers, and then from freelancers to out of business.
What it does : Allows freelancers to keep providing their services safely from home.
How I built it : HTML was used as a skeleton for the website with the help of css to customize it. Js was used to be able to interact with the website, while ajax was used to call server side php code to be able to retrieve and save data to the data base (mysql).
Challenges I ran into: Importing data from the database
Accomplishments that I'm proud of: Being able to succesfully organize the great amount of work in order to accomplish as much as possible in time.
What I learned: Designing a project, planning a project, Ajax for beginners, Ajax call php
What's next for Job Flow: Help growing local economy and encourage rare talents to profit by starting a small business.
Built With
ajax)
css-(bootstrap4)
html
js-(jquery
mysql
php
Try it out
unsevered-tacks.000webhostapp.com
drive.google.com | Job Flow | Freelancers are now out of business due to economic issues and pandamic lockdowns. We aim to create a platform to allow small local businesses to continue providing their services from home. | ['Elissa Bou Karam', 'Harout Topjian', 'Robert Chahwan', 'Christian Hajj'] | [] | ['ajax)', 'css-(bootstrap4)', 'html', 'js-(jquery', 'mysql', 'php'] | 6 |
9,921 | https://devpost.com/software/safeshop-vyaepn | Example of GUI
Logo
Inspiration
Our current situation in Italy... Whenever we go out for shopping, we have to wait a big queue before being able to enter the shop. At the same time, the shop owners are losing profits because of the constraints on the maximum people allowed inside the shop.
What it does
The application "SafeShop" should minimize the average waiting time of customers in the queue of a shop and maximize shop owner's profit.
How we built it
The presented demo was built in Matlab.
Challenges we ran into
Implementing the constraints on the maximum people for each section was not as straightforward as we tought, since customers can choose more than one section before entering. It took some time before we figure out a solution.
Accomplishments that we're proud of
Each member of the team had its own sub-goals and everyone contributed at the best of its possibilities to the completion of the prototype and the supporting material.
What we learned
The seminars were really interesting and provided us valuable knowledge
What's next for SafeShop
The next step would be the improvement of the code and its interaction with the GUI, which should be improved aswell. The app should be developed for Android and iOS in order to work properly.
Built With
matlab
Try it out
drive.google.com | SafeShop | The idea is to help the communities, especially the shop owners to reduce their economic losses due to the restrictions related to the maximum people allowed inside the shop. | ['Antonio Pepiciello', 'Carmela Bernardo', 'MUHAMMAD ABDELGHANY'] | [] | ['matlab'] | 7 |
9,921 | https://devpost.com/software/cloud-manufacturing-scheduling-system | Cloud Manufacturing (CMfg) Operation Model
Procedure of scheduling in cloud manufacturing (CMfg)
Inspiration
What it does
How I built it
Challenges I ran into
Accomplishments that I'm proud of
What I learned
What's next for Cloud Manufacturing Scheduling System
The idea is the purpose behind a PhD research I'm conducting. It's based on employing artificial intelligence techniques for scheduling resources in cloud manufacturing platforms. CMfg is a service-oriented technology for automating the process of manufacturing through a pool of configurable virtualized resources with the minimum intervention of service providers.
Offering manufacturing resources for use overseas allows for cheaper manufacturing, reduces prices, reduced transport and shipping, specially in turbulent times like these days. Instead of putting shipping activities on hold, manufacturers can place job batches remotely at distribution locations, by utilizing manufacturing resources shared on the Cloud Manufacturing platform.
CMfg is a manufacturing paradigm over networks that connects distributed resources and capabilities, by using the new generation of information technologies such as big data, IoT, cloud computing, and the Internet.
Videos and demo links are provided to clarify the concept and the idea. The actual system is still under design.
Built With
ai
cloud
google
simulation
Try it out
bit.ly | Cloud Manufacturing Smart Scheduling System | Synthesizing an intelligent algorithm for a cloud manufacturing platform, where manufactureres from around the world can share all kinds of resources for exchange of knowledge, experience, and tech. | ['Rania Al-Maghraby'] | [] | ['ai', 'cloud', 'google', 'simulation'] | 8 |
9,921 | https://devpost.com/software/covid-19-test-9etf7p |
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Inspiration
The pandemic has spread as much as it has because people did not take it as seriously as they should have. Even right now, most people do not know the symptoms, and what they need to do, if it is likely they have been infected. This project aims to remove ignorance, a pillar supporting the spread of the virus.
What it does
Team Lacasa's solution is an android application that asks a couple of yes/no questions about the symptoms and other factors that indicate a likelihood of infection. A score is attached to each question, and next steps to follow are given depending on the total score at the end of the test.
How I built it
It was built in the Android Studio IDE using Java.
Challenges I ran into
A major challenge was power supply, because of it, our team could only work for 2 hours a day.
Accomplishments that I'm proud of
Despite the limited time we had to work on it, we managed to finish the project.
What I learned
Apart from knowing more about the symptoms of the virus, no one on the team had previous experience with android development, we can say we do now.
What's next for COVID-19 Test
Team Lacasa chose the Android platform because a majority of the world's population is privy to it, and more people can be enlightened this way. With the help of medical professionals and the publicity from winning ieeesightegypt, more content can be added and more people reached.
Built With
android
java
Try it out
drive.google.com | COVID-19 Test | An easy way to check oneself for the possibility of being infected by COVID-19, and snippets of valuable advice whatever the case. | ['Daniel Tarerefa', 'Jerry Ebikari'] | [] | ['android', 'java'] | 9 |
9,921 | https://devpost.com/software/peacefood | The first Logo
Our Map
Our UI
Inspiration:
Economic Impact of the pandemic has huge cost on the economy and a lot of people are loosing their jobs, plunging families into poverty and food insecurity.
What it does
Our app joins the digital social movement of #QuarantineBaking and #BakeCorona to connect apprentice cooks across the world in their fight against COVID-19 from their kitchen where they can feed families in need.
How we built it
We built the demo on the Figma platform. Check out our demo on the link below.
What's next for PeaceFood
The Sahtein app brings the Arab identity closer in times where it is tested the most. With your help, we are aiming to launch within 2 month.
Video Pitch:
https://youtu.be/20oC_uvjuJw
Project Presentation:
https://drive.google.com/open?id=1_IYA20vmV2yk6j2bLTitgbzVoi1KhC1r
Project Details
https://drive.google.com/open?id=1LZJ9vnmrW3V5lecqGme0l0OcMqZYcAQ3
Application Brief:
https://drive.google.com/open?id=1avDfYrgoUt4-m1_2EkMgKiQjCu1ksRIA
Application Demo:
https://www.figma.com/proto/ban6YRJc5ix3Fx0BAjooH9/PeaceFood?node-id=1%3A26&scaling=scale-down
Try it out
www.figma.com | PeaceFood | A food App that helps you discover food from new places and people. | ['Rayan Hanna', 'Ebrahim Karam', 'Kevin Chahwan'] | [] | [] | 10 |
9,921 | https://devpost.com/software/tutorbook-g9756n | Search view
Home page
Volunteer sign-up form
Pupil sign-up form
Tutorbook
Tutorbook
is a free, online platform that connects students with expert mentors and volunteer tutors.
We're connecting 9-12 students with expert mentors to collaborate on meaningful (summer) projects that they're both passionate about (e.g. writing a research paper or releasing a music album together).
We're also making sure that no one loses out on education amidst COVID-19 by connecting K-12 students with free, volunteer tutors.
Aspect #1: Volunteer Tutoring
This was created a while ago for a different hackathon, but I figured I might as well include it here as well (to make this project description comprehensive):
The problem
Students no longer have the individualized support teachers usually have given
(when they met face-to-face)
Teachers can no longer attend to each student individually; some students are
falling behind
The solution
Support those students by connecting them to university students and
professionals also confined in their homes
Enable teachers to request one-on-one help for students they know are
struggling
We're currently partnering with
Project Access
,
the UK's CTI
,
Austria's StudyRoom
,
Singapore's Learnpanion
, and
School Closures
to connect students affected by COVID-19 with free, one-on-one, volunteer tutoring.
Aspect #2: Project Oriented Mentorship
This is what I'm really excited about (and this is what we built for this hackathon).
From
"IT'S TIME TO BUILD"
:
We know one-to-one tutoring can reliably increase education outcomes by two standard deviations (the Bloom two-sigma effect); we have the internet; why haven’t we built systems to match every young learner with an older tutor to dramatically improve student success? —Marc Andreessen
I just built such a system. I've created Tutorbook to connect every student with an expert mentor and (as needed) qualified, volunteer tutors.
We're connecting 9-12 students with experts (like you) to collaborate on cool, meaningful (summer) projects (e.g. a web app or research paper) that you're both passionate about.
Lots of student summer plans have been dashed due to COVID-19. This'll be an amazing opportunity for them to work with an expert (e.g. you) on something they're interested in (e.g. a cool startup idea).
I'm calling it "project oriented mentorship." Both the student and their mentor are passionate about some field (e.g. computer science or marketing) but the student doesn't have the experience, connections, knowledge, or resources that the mentor has.
From Paul Graham's
"What You'll Wish You Had Known"
:
If you'd asked me in high school what the difference was between high school kids and adults, I'd have said it was that adults had to earn a living. Wrong. It's that adults take responsibility for themselves. Making a living is only a small part of it. Far more important is to take intellectual responsibility for oneself.
If I had to go through high school again, I'd treat it like a day job. I don't mean that I'd slack in school. Working at something as a day job doesn't mean doing it badly. It means not being defined by it. I mean I wouldn't think of myself as a high school student, just as a musician with a day job as a waiter doesn't think of himself as a waiter. [3] And when I wasn't working at my day job I'd start trying to do real work. —Paul Graham
I agree with PG completely!
But most students don't have other cool projects to work on/learn about. Most students would be thrilled to work on some of the startup ideas I've seen pop up around here. But they don't know about them.
And they won't know about them unless we do something about it.
Here's how it will work:
The expert mentor (e.g. an awesome Indie Hacker like you)
signs up here
and posts about a project they'd love to collaborate on with a student (e.g. an app or startup idea).
The student searches (e.g. "I'm interested in CS" or "I want to work on marketing") and requests an expert mentor.
The mentor then chats with the student, their parents, and points the student towards resources to get started (e.g. tutorials, documentation, GitHub repositories, etc).
The student and the mentor work closely together to reach their goals for their project (e.g. successfully launching that app or startup idea).
You can read more about my ideas on
this GitHub RFC
or
this Indie Hackers blog post
.
Inspiration
This (the project oriented mentorship idea) was based off of my experience with
Luke Hsiao
(a Stanford PhD candidate) writing
this paper
together. I had no Python experience whatsoever beforehand but was able to learn quickly and contribute quite a bit (e.g. I'm the 3rd author on
that paper
). And now I'm best friends with Luke and will go to him whenever I have questions about CS or want someone to bounce ideas off of (e.g. these ideas were first validated by his feedback). I want to recreate that relationship for every student--regardless of their socioeconomic status, connections, etc.
Tech Stack
Languages
Typescript
- As our language of choice
(mostly for static typing, stronger linting capabilities, and the potential
for beautifully detailed--and completely automatically generated--
documentation). Typescript is also
well supported by
Next.js
and
React
.
Sass
- For styling components (i.e. CSS on steroids).
Sass, like Typescript, is also
well supported by Next.js
out-of-box.
Frameworks
React
- As our front-end framework.
Next.js
- To easily support
SSR
and
other performance
PWA
features.
Tooling
Lerna
- To manage and re-use React components across
repositories; mostly just to migrate code from this project back into
Tutorbook
when we get the chance.
ESLint
- For code linting to avoid
common mistakes and to enforce styling. Follow
these
instructions
to install it
in the text editor of your choice (such that you won't have to wait until our
pre-commit hooks fail to update your code).
Database
Google's Firebase
- For their
NoSQL
document-based database
,
Authentication
, and other
useful (relatively drop-in) solutions.
Built With
algolia
firebase
handlebars.js
lerna
next.js
react.js
sass
sendgrid
typescript
Try it out
tutorbook.org
github.com | Tutorbook | Web app that connects students with expert mentors and volunteer tutors. | ['Rashmit Shrestha', 'Nicholas Chiang', 'Zia Truong', 'Sanchit Pandey'] | [] | ['algolia', 'firebase', 'handlebars.js', 'lerna', 'next.js', 'react.js', 'sass', 'sendgrid', 'typescript'] | 11 |
9,921 | https://devpost.com/software/trovify-charcuterio | Landing page
How it works
Become a contributor
Find supermarkets with available items
Save a timeslot
Welcome back from shopping!
Contribute
Inspiration
COVID-19 global panic buying has emptied shelves of basic staples in all supermarkets, leaving families, high risk groups and individuals without access to the most basic needs. Supply chains are implementing measures to increase their stock levels and safety protocols but fear of shortages of food and services are making their stock on site fluctuate every week and supermarkets become high-risk infection areas.
What it does
Trova.do is a platform that helps users optimise their visit to the supermarket, by informing them about item availability in their nearest shops, while reducing their exposure to the virus, eliminating unnecessary movements to risk areas.
How we built it
User research to 50 people from different parts of the world.
Stock levels:
Toilet paper, pasta, rice, flour, yeast, bread, tins of preserved food, hand sanitiser and other cleaning products are the main items people have been having trouble finding in their local supermarket.
Paracetamol, masks and gloves have been sold out in specialised shops.
Safety equipment:
46% of people don't have the necessary protective equipment
they can use when they're out.
Only 7% percent of people have a full protective equipment.
13% of people only have gloves.
17% of people only have masks.
17% of people have masks and gloves.
Exposure frequency:
16% of people did not visit the supermarket in the past week.
52% of people went to the supermarket once in the past week.
32% of people went to the supermarket more than twice in a week.
Risk groups:
People with no protective equipment went to the the supermarket x1.87 times more
than people with some protective equipment.
People with no protective equipment went to the supermarket 1.11 times per week on average, while people with some protective equipment went 0.59 times per week on average.
Define & Develop
Based on this data, we know the majority of people are trying to limit their visit to the supermarket. However, finding the items sold out in-store, they are forced to go several times in a week.
We want to search for the data that will generate stock levels.
We want integrate the map with supermarket near user's location.
We want to filter the supermarkets based on items availability.
Design and develop the UI.
Challenges we ran into
Retrieving enough data from supermarkets websites and locating/filtering them in the map.
Not sleeping much.
Making sure the stock availability is true and updated frequently.
Identifying users that have recently been in a supermarket and ask them about the availability of certain items.
Reaching out to the elder community.
Trying not to get overwhelmed by the COVID-19 emergency and all the needed features and build a MVP.
Accomplishments that we're proud of
Contributing to open source projects, like Gridsome.
Helping any way we can to fight the COVID-19 outbreak with our resources and skills.
What we learned
More people than we thought are exposed to high-risk hotspots.
Even though supply chains keep increasing their stock levels, the most essential products are still sold out.
TailwindUI is awesome when you need to build fast.
Adding more than one language to the site.
What's next for Trova.do
Add pharmacies to the list.
Add more supermarkets to the list.
Scale the website to a global level and add more languages.
Let people become active trusted contributors, gamifying the process of updating stock levels and help the next supermarket visitors.
Let people ask for specific item availability that we might not be currently tracking.
Help supermarkets get a more even distribution of people in their time slots, avoiding peak hours.
Help supermarkets analyse and predict users behaviours by neighbourhoods.
Set up a digital queue or online shopping system.
Built With
abstract
figma
firebase
gridsome
mapbox
sketch
tailwindui
Try it out
trovado.now.sh
github.com | Trova.do | Optimise your supermarket & pharmacy visit during the COVID-19 quarantine. Find everything you need and reduce unnecessary movements to risk areas. | ['Nestor Vera', 'Hanseo Park'] | ['Track Runner Up: 2nd Place', 'Highlighted Project'] | ['abstract', 'figma', 'firebase', 'gridsome', 'mapbox', 'sketch', 'tailwindui'] | 12 |
9,921 | https://devpost.com/software/education-wglupq | This is the sign in option
Teachers dashboard
A dashboard for chosen courses
For uploading Materials
Inspiration
Staying indoors all day has been quite challenging with limited access to educational resources, low network coverage and power supply. Less effort is being made to help we the students cope with our studies.
As the day progresses, students tend
to forget even the slightest thing such as our student identification number(Matriculation number), what more can be said about our studies and I miss my school library.
So we decided to build a friendly website that allows a one on one interaction between teachers and students, and where students can get necessary updates and educational resources at their finger tips.
## What it does
It allows students to subscribe to courses being offered on the dashboard, to get updates relating to their chosen courses and other relevant information when uploaded by the teacher.
It makes available education resources in different formats such as lesson videos and notes, audios, visuals,text(ppt,word,pdf and doc formats) and slideshows uploaded by the teacher.
It provides an icon button for Course, Assignment, Materials, Timetable, Quiz/Assessment and Notification.
It notifies the student on lesson scheduled for each day based on the timetable and relevant updates as well.
It provides a live chat and video option for real-time interaction between teacher and student .
In a scenario where a student misses an online session, he/she can catch up, since the session will be recorded,and watch at his/her convenience.
## How we built it
It is built with html, Css, javascript, Node js for back-end, a sprinkle of glitch and a spice of love and support from everyone. For Database,we used firebase For hosting, we used heroku We made used of our faculty and departmental course codes and titles from level 200 - 500 and lecturers name.
## Challenges we ran into
We are used to physical hackathon, this is our first online hackathon, so it was quite overwhelming but we achieved our goals. We had a little bit of communication issue because of distance while working on this project.
Accomplishments that we're proud of
We built our first project online.yeah!! We can say that we helped the educational sector fight against COVID-19 and we are proud of it.
What we learned
It was my first time getting to know glitch and other languages as well. I was ecstatic
What's next for OnlineSch
For it to be used globally
Incorporate an App to work together with the site
To ensure that it is properly working
Built With
bootstrap
css
firebase
glitch
html
javascript
node.js
xml
Try it out
github.com | OnlineSch | OnlineSch bridges the communication gap between teachers and students. This platform features live stream of lectures and real-time interaction between teachers and their students. | ['Chino Ikwuegbu', 'victor Victor agbenro'] | [] | ['bootstrap', 'css', 'firebase', 'glitch', 'html', 'javascript', 'node.js', 'xml'] | 13 |
9,921 | https://devpost.com/software/3d-health-hack | this is a photo of my mother Dr ibtissam and I am very proud of her/ shes my secret power
Doctors using our face shield
production face shields
3D printed face shield
mass production help of Lebanon response team
main corona virus center in lebanon Hospital Rafic Hariri accepted the design of teh face shield, and need large quantities
Superokk logo
some web photo
Some web photo
We have better quality videos in the YouTube channel
https://www.youtube.com/watch?v=QcwDAETHzvg
what are main solutions proposed?
1_ Self employment job opportunities (during and after the covid_19 period)
2_ Provide to
hospitals
personal protection equipment's. (specially in countries of bad economical situation)
Story:
The progress is divided into phases we are now at phase 4
Phase 1:
After the lock down of countries due the covid_19 shipping was not an option. Solutions should be cheap and Manufactured in the country. we used 3D printing to solve this issue. (you may think that 3d printing is slow and is not efficient for mass production but we invented a 3d model that reduces the time of 3d printing of Personal protection equipment face shield from 6 hours to ~2 min).
phase 2:
After that our country Lebanon was not able to afford to buy face shields and ventilators along with other medical equipment's. here a team of professional engineers where formed (Lebanon response team) and we proudly implemented most of the projects including the face shield using the 3d technology. We where able to support the main corona virus center in Lebanon with the needed equipment's. It was all done remotely and here is the key for the phase 3.
phase 3:
After that a separate team was formed ( France, Holand , Lebanon) to participate in a hackathon sponsored by the " Freiderish Noamann foundation" . The Idea now is how to transmit the same success to other countries "Remotely". And we did it, we won. We where able to get sponsored . We are building a platform (website ) links 3d printer owners to people who need 3d printed things.
Advantage of such website we will be able to :
1_ Provide self employment job opportunities during and after the covid_19 period.
2_Help specially Countries that are facing bad economical situation to provide 3D printable personal protection equipment's without shipping row material!
3_ Creating a worldwide community that is interested in 3D technology.
the estimated time for the website to be done is ~4 weeks from today
Meanwhile we should proceed to phase 4 :
phase 4: Currently We are here - Marketing strategy- Social media :
_YouTube channel:
_we realize after studying the market that , we need the process to be very interactive to succeed.
Since we are more into the "polling " business model concept than into the " pushing "concept we believe that building an educational platform on YouTube will generate lead's to the mechanism sustainably. So the main idea now is to provide high value content on the YouTube platform to generate lead and build a Brand.
technique to be used: After studying the way YouTube promote it's videos.
(based on views and how much it's interactive).
*
1_ Animation: *
Higher the efficiency (click throw rate).
2_ Interactive videos:
To maximize interactive part we will include the new technology of interactive video.
3_Business startups:
we will provide users with methods for effective uses of the program.
4_Multi-linguistic:
we will upload in several languages so we can spread the message to the maximum.
5_Daily uploads:
YouTube promote videos of users who uploading more (High quality content).
Main points
How the website will help medical field?
web will locate institution and people who need 3D printed solutions (example face shield)
What differentiates us?
• Marketing strategy that we developed this weekend.
• The sustainability in the business model.
• Community : We are joining people that has same goals together on this platform
_ one of our goal is to help the medical : even if it is a doctor that needs 3d modeling to medicine teeth of his/her patient.
Team and how we started briefly :
Clearly results started to appear hospitals show a need and we where able to provide them with their needs.
So a team of expert was found to make this solution achievable by other country.
Team: Ezzedin ayoubi senior lead Senior Lead in development at KLM ,DEV Team mentor
Hassan Hallal Team Leader at ASSYSTEM E&I ,Business, Management(mentor in business management )
Ali Hussein: mechanical engineering student founder of Superokk.
3D printer owners: we have a big database of people who are welling to start providing Hospitals and even people.
Any skilled in anything he is thinking that he can be an added value kindly don't hesitate to contact us.
Accomplishments that we're proud of:
We are proud that we where able to provide main covid_19 center in Lebanon with the face shields needed last week, and that we are able to make some profit to make it sustainable.
Won several competition
Ranked Top 15 in worldwide hackathon of IEEE
What we learned:
How to make from the weakness a point of strength.
Group work using social distance.
tech to use in execution
_ In labs doing experiments for compatibility if someone want to add a new product (like sterilizing test)
_the majority of it will spent on software's that will make the process easier:
we list:
_upgrade an animation software called **** (I have it but we need to upgrade enterprise level and we need the color versions)
_powerful animation app called **** that will give us the ability to make character moving (and to tell stories ,to make the contempt extremely easy to understood)
_this software is extremely powerful (specifically for us). 3D printing mean customization ,and this give us the abilities to customize any video to all our viewers!!
_will help translate ,** text to speech ,speech to text , join every slide to the voice inserted **without the suffer and the time loss of meshing
_intro videos and finalizing in high professional videos in matter of minutes (first to do that it was taking days !!! )
we want to make a difference in the digital age.
The Digital Health is extremely important at this time.
_It will simplify and accelerate the processes.
_No shipping requirements and fits specially in countries in bad economic situation.
_Higher efficiency ,Lower time
_ More job opportunities
never forgot: dream big you can fly
environmentally friendly
3d printing materil we are using are almost 100% (disintegratable,and recycable). (good for nature).In addition that we have other backup plans.
Mentors and sponsors
thank you for the great effort you are putting without these competitions we where not able to progress so far.
Built With
angular.js
firebase
java
www.superokk.com
Try it out
www.superokk.com
drive.google.com
drive.google.com
drive.google.com
drive.google.com | superokk Health | website link between 3d printer owners and people who need 3d prints | [] | [] | ['angular.js', 'firebase', 'java', 'www.superokk.com'] | 14 |
9,921 | https://devpost.com/software/ventilator-fastzm | Ambu bag
checking dimension before wiring
Trial with external power source(proof of concept)
Inspiration
What inspire us is the serious situation the whole world is facing today due to COVID19. And due to the over crowded hospitals and the lack of ventilators we tried to figure out something that could help in this problem.
What it does
This device use the standard ordinary Ambu bag (which is manual) and some of the shelf electronics (arduino, motor driver and DC motor) to make low cost easy to make small ventilator that runs automatically and can be controlled to adjust how many breath per minute that reaches the patient.
How we built it
We used the normal Bag valve mask that use normal air and also have input for oxygen concentration with reservoir bag for oxygen, it also have a valve for reducing pressure if a child patient is using it. We designed parts for the ventilator body and we used 4mm CNC laser cutted wood for less time and cost (those parts can be 3D printed but will require more time). Also 3D printed parts are designed for body parts assembly and fitting and also for hose extension for the mouse mask. for controlling the device we used arduino uno and a L298 motor driver which is easy to connect and available everywhere.
Challenges we ran into
One of the challenges is the connectors design, we wanted it to be universal and to work on every standard dimension hose and the common ambu bag. Other challenge was to print and try each part in limited time to proof the concept.
Accomplishments that we're proud of
We are proud that this project will be opensource for anyone to replicate and use it. we also proud that we made everything from scratch.
What's next for Ventilator
The next step is to make it more reliable and easier for assembly with one power input from Ac source like the normal plug. We also want to add batteries so it can run for like 120 minutes in case of power lose.
Built With
3dprinting
arduino
autodesk-fusion-360
c++
cnc
driver
motor
Try it out
github.com
drive.google.com | Low cost Ventilator | Easy to make ventilator help in the mild cases of COVID-19 | ['Abo-bakr Emara', 'abdallah assem'] | [] | ['3dprinting', 'arduino', 'autodesk-fusion-360', 'c++', 'cnc', 'driver', 'motor'] | 15 |
9,921 | https://devpost.com/software/donw-app | DonW app logo
DonW-app
When detecting a case infected with Coronavirus, among the most important challenges facing the medical staff is
to know the people who have contact with the infected person
and the virus was probably spread to them
our application show prevention and symptoms
of this virus and allow people to know all hotspot
that are close to them
Our solution is to develop a mobile application that enables you to know if you have visited a place at the same time that an infected person visited it, and the virus was probably spread to you
Which will contribute to the detection of infected cases quickly
BACKEND : Django
FRONTEND : Flutter
Built With
django
flutter
heroku
python
Try it out
github.com | DonW-app | mobile application that enables you to know if you have visited a place at the same time that an infected person visited it | ['HOURIA EL ANSARI', 'Anas Mansouri', 'Mohamed Hammadi'] | [] | ['django', 'flutter', 'heroku', 'python'] | 16 |
9,921 | https://devpost.com/software/community-hero | Messenger chatbot
SMS chatbot
Webapp
Delivery portal
Inspiration
When the pandemic began, it was clear that the elderly would suffer disproportionately - not only are they the age group most at risk from the virus, but they are also the likeliest to be living alone, meaning they have to do their own groceries. Of course, supermarkets have shown to be transmission vectors for the virus, making a simple essential act like picking up weekly groceries something that can lead to catching Coronavirus. And this is of course, a much more dangerous move for the elderly, since the mortality rate increases exponentially with age. One could suggest online ordering as a solution, however this age group is likelier to be tech-illiterate, and hence conventional online ordering is less likely to draw them in, due to their unfamiliarity with it combined with confusing site layouts. That is why we built CommunityHero - a truly accessible online ordering solution, tailored to keep the most vulnerable parts of our population safe.
What we do
CommunityHero provides 3 main interfaces for online ordering - firstly, a smart Messenger chatbot which provides product images, helpful tips and uses Machine Learning to help parse each customer's shopping list. Secondly, we built an SMS interface for those not on Facebook/not on the Internet, with approximately the same functionality as the Messenger chatbot. Lastly, we built a
webapp
which works like traditional online ordering sites, albeit with a simpler layout.
Messenger
SMS
All of these interfaces, each one designed to tailor to the needs of our target customer (an elderly person with little to no tech literacy), link to a
web interface showing all pending orders
. This is accessible by our “Community Heroes” - part of our volunteer delivery network. We currently plan to partner with local NGOs in every area we serve to help find a large number of Community Heroes quickly and efficiently.
Community Heroes can log in on a web interface and see all of the orders available on a map and choose which ones to order. Upon choosing an order, they can claim it, so that they can see the full order details. The system will also then send a message to the original customer saying that their order has been claimed by someone. In order to further decrease the chances of infection between the community hero and the customer, we present the “Community Hero” a set of guidelines that they need to follow to ensure the process is safe, including provisions to wear PPE.
How we built it
We use an Android phone as the SMS gateway, which receives incoming SMS messages and forwards them to the backend, built using Django and hosted on Heroku. We use NLP to search for the products requested in the products available, and choose the best combination that minimizes price and distance. The searching is done by splitting all strings into N-grams and using the Jaccard Distance. Further, based on what products are most commonly in carts, we made a product weighting system, based on how popular each item is. For example, even though Soy milk and Skimmed milk would both be results to the search 'milk', the user is more likely to want skimmed milk. This is done automatically based on the collective current shopping carts of all users. This allows for trends to remain as trends (for example, hopefully, disinfectant products will not be so common in 2-3 years)
Our chatbots are stateful - this means that the context from the previous messages is understood in order to find the state in which the conversation is. For example, the bot knows that the user is still completing his/her profile, so it understands that an incoming message containing 'Yes' is not something to search for, but rather an answer to a previous question.
The frontend communicates with the backend RESTfully.
Demo
Instructions on how to run the demo are available
here
Challenges
It was difficult to find a way to find a viable business model, since it is based on human interest for others, and volunteering, which may be difficult to promote. However, since we are in the middle of a global pandemic, it is a lot easier to get people to dedicate their time than before.
Currently, our business model relies on attaining revenue through small commissions stores will pay whenever a customer shops with them through our platform. This revenue will be used to help provide PPE (masks & gloves) and support to our Community Heroes, who we will source via local NGOs. The benefit to this approach is it allows us to scale faster than usual - NGOs are often more efficient when it comes to getting together a large number of volunteers, and we are certain that for a
A technical difficulty we had was the fact that for Facebook Messenger to accept our messages / to send us messages, it needed to be hosted over HTTPS. Therefore, it couldn't be tested locally without a domain name. Hence, every time we changed something in the code we needed to push to GitHub, and redeploy the whole backend, which took 2-3 minutes every time, no matter how small of a change we wanted to make.
Another thing that we were anxious about is the Facebook App Review. This is a process needed in order to make an app that uses the Facebook API live. However, this is a manual process that may take up to 2 weeks! We didn't expect the process to finish in time for the demo, so we also implemented a process through which anyone can send us their Facebook profile, and they would be added as testers. Fortunately, the process finished a few hours before the submission deadline, so even though it was already implemented, we don't need to use this long (and manual) process of adding testers, since our chatbot is now public.
Accomplishments
Awarded at the Greek Crowdpolicy Antivirus Hackathon amongst 50 teams!
We were able to make significant progress on the chatbot within the past 2 days.The idea was refined and revised multiple times, and we feel that the idea itself is quite unique - we certainly haven’t been able to find an equivalent alternative on the market. Even though there are a few similar ideas in the hackathon, with the same concept of crowd-delivery, we believe that our range of ordering methods adds significant value to our product.
What we learned
Make REST APIs
Use the FB Messenger API to send messages
Go through the FB verification process
Use, manage and launch WordPress WooCommerce site
Hosting on Heroku
Using NLP libraries
What's next
Partner with supermarkets
Build in navigation into deliverers web interface, make it into a cross-platform mobile app
Partner with local NGO to source first CommunityHeroes and bring product live ASAP
Who we are
We are a team of high school students from Cyprus interested in the social good and try to contribute, in whatever way we can, to as many people possible in these dire times we live
Any feedback is welcome here as a comment, or shoot us an email at
feedback@mail.communityhero.live
:)
Built With
android
bootstrap
django
facebook-messenger
heroku
java
jquery
leaflet.js
natural-language-processing
php
postgresql
python
rest
sms
woocommerce
wordpress
Try it out
github.com
communityhero.live | Community Hero | Community driven delivery service, focused on providing access to the essentials, such as groceries, to the most vulnerable sectors of the population, by accessible ordering methods | ['Christos Falas', 'Deniz Akansoy', 'Andreas Lordos'] | [] | ['android', 'bootstrap', 'django', 'facebook-messenger', 'heroku', 'java', 'jquery', 'leaflet.js', 'natural-language-processing', 'php', 'postgresql', 'python', 'rest', 'sms', 'woocommerce', 'wordpress'] | 17 |
9,921 | https://devpost.com/software/quarantine-social | Inspiration: Providing immediate and future solutions over covid-19 Pandemic Crisis.
People are just confused of what is happening, some felt its the end of time.While schools are closed, street lockdown, business not moving, everything is hanged on. To crown it all, when you online, you will be seeing cases of infected people, deaths etc. No testimonies of People who just recovered. People need to know what what our Biotechnological companies are doing. Most Africans dying of hungry virus due to luckdown. There is alot of problem to this. I felt I could solve some major issues and hence
Quarantine Social
was born
What it Does
Solving Immedate Covid-19 Virus Pandemic Crisis and issues:
They are alots of things that can be done to help contain Covid-19 Virus cases.
1.) Educational Posts, Blogging and Enlightenment:
People need to be educated and enlightened on the danger of all this Covid-19 Virus infections.
To this effects, we created an application to
allow community to educative post, blogs etc. to the community via, photos, Videos, Posts updates
while allowing the community to respond via likes,
comments, replies etc. For instance one can share a video educating community members on how to contain the virus eg
via social distancing, washing of hands etc.
2.) Food Distributions Post Updates:
Due to this Covid-19 pandemic, some people are dying of hunger virus
because they do not have money for feeding especially in Africa. This Category allow community members to
share foods online. For instance one can create a posts or video updates saying I have
10 cups of rice.
stating his address in the
post message while the needy responds in the comments sections and vice versa.
3.) Drug and Vaccine Posts Updates:
The world needs to know what is going on in the field of Bio-technology.
Has vaccine been discovered. what about clinical trials vaccine.
which companies are on the frontline for vaccine/drug race.
For instance one can share Post, photos or video updates on Mordena Clinical Trial Vaccine,Johnson & Johnson
Trial Vaccine etc.
to give
community members hope while allowing other community members to respond via likes,
comments, replies etc.
4.) Sports Posts Updates:
Due to this pandemic and lockdown people can no longer engage in excercise
that can improve theirhealth.
this category allows members to share informations via post,
photos or video updates on different excersies good for the body while allowing other community members to respond via likes,
unlike, comments, replies etc.
5.) Testimony/Goodness Updates:
Almost everything I see online is number of cases, deaths etc. this tends to put
anxiety, Blood Pressure, fear in the mind of people. Most people that died was not as a result of this illed virus but
they have notion that once infected, you are gone. this limits their tenacity to humanly fight this virus while still
counting on God. To this effect, we created this category to allow community members who must have survive this
virus to share their experiences and good news while encouraging others to be calm and faithful to God.
6.) Donations:
Donations can be anything eg. money, gift etc. The application allow the community members
and philanthropist to donate money that will be use to assit community affected by this pandemic.
The Application uses
Paypal Payment Gateways
to collect the payment donations.
The site Admin has to update his Paypal wallets Email address and other information's from the admin dashboard.
7.) Immediate Connections to Site Admin(Planetry Experts) Social Networks:
On the landing page,the applications allows the community members to reach out to
Planetry Experts on their various social media Eg.
Facebook, Whatsapp, Twitter
to learn and gather more information's from there on how to keep the planet safe.
All the site admin has to do is to login to the admin dashboard and updates all their Social Links so as to reflects on the landing page.
8.)Contact Us Mail:
Community members can use this to send emergency messages to the site admin on environmental emergency
situations. All this forms has a built-in internal defense against spam-bots.
All the site admin has to do is to login to the admin dashboard and updates all their
Contact us email address,
Phone numbers
etc so as to reflects on the landing page. This will enable site admin to receive messages straight to his email addresses
Solving Future Pandemic Crisis via Whistle Blowing:
I was reading about origin of covid-19 virus and I came across a
CNN
posts on how Chinese
Governments tries to silence doctor
Li Wenliang
who boldly blows whistle on the novel corona virus so that world will take actions and protective measures.
CNN Source Here:
https://edition.cnn.com/2020/02/03/asia/coronavirus-doctor-whistle-blower-intl-hnk/index.html
Some other doctors in China could have done the same but just that they are afraid of their governments and the same thing could happen to other Whistle Blowers in any other government
oppressing countries.
Solutions:
Posting, Sharing Educative and emergency information's anonymously.
We provide a system to allow people with good mind to post their Environmental,
planetry observations, hazards in the form of Posts, Blogs, photos, videos etc. anonimously
without anyone knowing it was you.
The Blogs, post will not be seen from the Whistle Blower profile so you have nothing to be afraid of anyone tracking your back. . Only the site admin can have access.
other community members can only comments, likes, replies etc. on the anonymous post without ever knowing who shared it.
How to use/test the Applications:
(For testing this apps, Mozila Browser is my best)
The applications has both Admin and members sections though some other features are yet to be implemented due to lack of time.
Accessing the application as Admin:
You will require to make registration with 8 digit access code
good1982
Without this access code, you cannot register as an admin.
The Admin form is protected with built-in spambot shields.
Accessing the application as a Member:
As a community members, Environmental Bloggers, Experts etc, you will have
to register with a valid email address. Upon registration, a verification link will be sent to your email address to complete
your registration.
Admin can do other minor customization's on the landing page.
More features coming soon as can be seen from the apps members and admin dashboards.
Devices already Tested:
Highly mobile responsive and works on all devices ranging from mobiles smart phones to desktop devices.
How we built it
This application was built using Bootstraps, css, jquery, ajax, php and mysql
challenges/ Issues Currently having on testing
My major issue is light. we always have power outage and this limit my ability and speed to add more features.
The app runs excellent locally on all browsers like
Mozila, UC, internet explorer 11 etc and some version of chrome.
For instance the Chrome in my laptops allows all the bootstraps files to load and the app is working excellent while chrome version in my desktop does not allow 2 bootstraps files to be loaded remotely saying error integrity check unless i loaded the 2 bootstrap files locally.
I know I can solve this little chrome issue later. its just some chrome browser issues
Accomplishments that we're proud of !
Its not easy to develop an application from a remote area where there is no light. I was in a luckdown just manage to code this
What we learned ?
I learnt that can I try anything no matter how difficult it might appear. My major problem is light
What is next ?
1.)I need to add ability of users to also like and unlike sub comments, replies to sub comments to all posts, videos , photos and updates being shared
2.) I need to add business social platform to get all the small businesses on board. I know how I can do this.
3.) Ability to Report Fake news: They are many online fake news every where with fake products. this needs to be curtailed as it creates serious confusion in the society. Some says Garlic can cure covid-19, others says bath with salt. I wonder oooooo.
My mother just come back and told me that her colleagues read some where online that rubbing olive oil will reduce the impact of corona virus. all this are fake and community or individuals are at risk.
4)They are many many more ideas. Thank You
Try it out
equationdev.com | Quarantine Social App | A Social app that provides 10 ways to solve immediate and future covid-19 Pandemic Crisis. | [] | [] | [] | 18 |
9,921 | https://devpost.com/software/pandamik | Your pandemic companion
Inspiration
Observations of recent events have lead us to the three most popular questions right now i.e:
Where can I get tested?
Should I get tested?
What places should I avoid?
What's Pandemik?
Pandamik at its core, is a web app that delivers a solution to all the problems raised through those questions. We are using the available COVID-19 APIs to inform our users of the nearest testing facilities, in addition to warning them of potential dangerous locations where many cases have been officially reported.
We also aim to shorten the gap between users and medical staff by giving them the ability to take a survey that will inform them of the likelihood of having COVID-19. If they score high on the survey, they will be recommended to seek testing and if they chose their answers will be sent to a medical professional for review and these applicants will then be contacted for a follow-up.
The survey will evaluate users’ health status using a point system. It is done in such a way to provide user friendliness and a simple way at gathering data about them. Upon entering the survey page, users will be prompted to answer a series of closed-ended questions pertaining to COVID-19 symptoms.
E.g: Are you experiencing bouts of dry coughing? Yes/No.
Each question has been assigned a value that adds up to 25, and depending on what the user has answered, their amount of points will fall into a range that tells them what to do. For example, if a user has gotten below 10 points, a message will alert them that they’re most likely fine and that they should just take it easy. However, if a user’s points fall within a range between 16 and 20 points, they’ll know that the best course of action is to seek a test, as to avoid any potential complications and risk suffering the full brunt of COVID-19.
In addition to our reliance on reliable APIs to get our data, a significant part of the Pandemik's data source will be its users. Pandamik has a robust solution that allows its users to pinpoint suspicious locations for other users of the app to see. To put this into perspective, imagine yourself walking down a marketplace and spot a potential virus carrier through visible and apparent symptoms. You'll be able to then mark this spot as an area that might be in danger of being exposed to COVID-19 and henceforth warn any users to avoid the area and even hand a tip to health officials to secure the area.
How it's built
We are using multiple COVID-19 APIs to get fresh and accurate information for our users. Furthermore, the help of medical professionals for the survey is used and with the help of Mapbox, we are giving our users a friendly interface so that they know what places to avoid, and where to go to get tested.
Challenges
Finding a medical team for help as well as making our users trust us with both their data and the information we are providing them.
Accomplishments and aspirations
We honestly just want to help make a change in this horrible situation no matter how small it may seem.
What's next for Pandamik
We hope that our platform will grow to be the go-to site for any future pandemic or biologically hazardous situation.
Built With
css
geojson
html
javascript
jquery
json
mapbox
mysql
php
Try it out
mrcrabz.github.io | Pandamik | Your Pandemic Companion | ['Fouad Khalife', 'robin geagea', 'Francis Sougué'] | [] | ['css', 'geojson', 'html', 'javascript', 'jquery', 'json', 'mapbox', 'mysql', 'php'] | 19 |
9,921 | https://devpost.com/software/deep-learning-drone-delivery-system | Results of our CNN-LSTM
Accuracy after training our model on 25 epochs
MSE of our CNN-LSTM
How we preprocessed data for our model
Data preprocessing
Picture of Drone
Inspiration:
The COVID-19 pandemic has caused mass panic and is leaving everyone paranoid. In a time like this, simply leaving the house leads to a high risk of contracting a fatal disease. Survival at home is also not easy: buying groceries is frightening and online ordered necessities take ages to arrive. The current delivery system still requires a ton of human contact and is not 100% virus free. All of these issues are causing a ton of paranoia regarding how people are going to keep their necessity supply stable. We wanted to find a solution that garners both efficiency and safety. Because of this, drones came into the picture(especially since one of our group members already had a drone with a camera). Drone delivery is not only efficient and safe, but also eco friendly and can reduce traffic congestion. Although there are already existing drone delivery companies, current drone navigation systems are neither robust or adaptable due to their heavy dependence on external sensors such as depth or infrared. Because of this, we wanted to create a completely autonomous and robust drone delivery system with image navigation that can easily be used in the market without supervision. In a dire time like now, a project like this could be monumentally applied to bring social wellbeing on a grand scale.
What it does:
Our project contains two parts. The first part is a deep learning algorithm that allows the drone to navigate images taken with a camera which is a novel and robust navigation technique that has never been implemented before. The second portion is actually implementing this algorithm into a delivery system with firebase and a ios ecommerce application.
Using deep learning and computer vision, we were able to train a drone to navigate by itself in crowded city streets. Our model has extremely high accuracy and can safely detect and allow the drone to navigate around any obstacles in the drone’s surroundings. We were also able to create an app that compliments the drone. The drone is integrated into this app through firebase and is the medium in which deliveries are made. The app essentially serves as an ecommerce platform that allows companies to post their different products for sale; meanwhile, customers are able to purchase these products and the experience is similar to that of shopping in actual stores. In addition, the users of the app can track the drone’s gps location of their deliveries.
How I built it:
To implement autonomous flight and allow drones to deliver packages to people swiftly, we took a machine learning approach and created a set of novel math formulas and deep learning models that focused on imitating two key aspects of driving: speed and steering. For our steering model, we first used gaussian blurring, filtering, and kernel-based edge detection techniques to preprocess the images we obtain from the drone's built-in camera. We then coded a CNN-LSTM model to predict both the steering angle of the drone. The model uses a convolutional neural network as a dimensionality reduction algorithm to output a feature vector representative of the camera image, which is then fed into a long short-term memory model. The LSTM model learns time-sensitive data (i.e. video feed) to account for spatial and temporal changes, such as that of cars and walking pedestrians. Due to the nature of predicted angles (i.e. wraparound), our LSTM outputs sine and cosine values, which we use to derive our angle to steer. As for the speed model, since we cannot perform depth perception to find the exact distances obstacles are from our drone with only one camera, we used an object detection algorithm to draw bounding boxes around all possible obstacles in an image. Then, using our novel math formulas, we define a two-dimensional probability map to map each pixel from a bounding box to a probability of collision and use Fubini's theorem to integrate and sum over the boxes. The final output is the probability of collision, which we can robustly predict in a completely unsupervised fashion.
We built the app using an Xcode engine with the language swift. Much of our app is built off of creating a Table View, and customized cell with proper constraints to display an appropriate ordering of listings. A large part of our app was created with the Firebase Database and Storage, which acts as a remote server where we stored our data. The Firebase authentication also allowed us to enable customers and companies to create their own personal accounts. For order tracking in the app, we were able to transfer the drone’s location to the firebase and ultimately display it's coordinates on the app using a python script.
Challenges:
The major challenge we faced is runtime. After compiling and running all our models and scripts, we had a runtime of roughly 120 seconds. Obviously, a runtime this long would not allow our program to be applicable in real life. Before we used the MobileNet CNN in our speed model, we started off with another object detection CNN called YOLOv3. We sourced most of the runtime to YOLOv3’s image labeling method, which sacrificed runtime in order to increase the accuracy of predicting and labeling exactly what an object was. However, this level of accuracy was not needed for our project, for example crashing into a tree or a car results in the same thing: failure. YOLOv3 also required a non-maximal suppression algorithm which ran in O(n^3). After switching to MobileNet and performing many math optimizations in our speed and steering models, we were able to get the runtime down to 0.29 seconds as a lower bound and 1.03 as an upper bound. The average runtime was 0.66 seconds and the standard deviation was 0.18 based on 150 trials. This meant that we increased our efficiency by more than 160 times.
Accomplishments:
We are proud of creating a working, intelligent system to solve a huge problem the world is facing. Although the system definitely has its limitations, it has proven to be adaptable and relatively robust, which is a huge accomplishment given the limitations of our dataset and computational capabilities. We are also proud of our probability of collision model because we were able to create a relatively robust, adaptable model with no training data.
We were also proud how we were able to create an app that compliments the drone. We were able to create a user-friendly app that is practical, efficient and visually pleasing for both customers and companies. We were also extremely proud of the overall integration of our drone with firebase. It is amazing how we were able to completely connect our drone with a full functioning app and have a project that could as of now, instantly be implemented in the marketplace.
What I learned:
Doing this project was one of the most fun and knowledgeable experiences that we have ever done. Before starting, we did not have much experience with connecting hardware to software. We never imagined it to be that hard just to upload our program onto a drone, but despite all the failed attempts and challenges we faced, we were able to successfully do it. We learned and grasped the basics of integrating software with hardware, and also the difficulty behind it. In addition, through this project, we also gained a lot more experience working with CNN’s. We learnt how different preprocessing, normalization, and post processing methods affect the robustness and complexity of our model. We also learnt to care about time complexity, as it made a huge difference in our project.
Whats Next:
A self-flying drone is applicable in nearly an unlimited amount of applications. We propose to use our drones, in addition to autonomous delivery systems, for conservation, data gathering, natural disaster relief, and emergency medical assistance. For conservation, our drone could be implemented to gather data on animals by tracking them in their habitat without human interference. As for natural disaster relief, drones could scout and take risks that volunteers are unable to, due to debris and unstable infrastructure. We hope that our drone navigation program will be useful for many future applications.
We believe that there are still a few things that we can do to further improve upon our project. To further decrease runtime, we believe using GPU acceleration or a better computer will allow the program to run even faster. This then would allow the drone to fly faster, increasing its usefulness. In addition, training the model on a larger and more varied dataset would improve the drone’s flying and adaptability, making it applicable in more situations. With our current program, if you want the drone to work in another environment all you need to do is just find a dataset for that environment.
As for the app, other than polishing it and making a script that tells the drone to fly back, we think our delivery system is ready to go and can be given to companies for their usage with customers. Companies would have to purchase their own drones and upload our algorithm but other than that, the process is extremely easy and practical.
Built With
drone
firebase
keras
opencv
python
swift
tensorflow
xcode
Try it out
github.com | Autonomous Drone Delivery System | An autonomous drone delivery system to provide efficient and virus-free deliveries. | ['Allen Ye', 'Gavin Wong', 'Michael Peng'] | ['Best COVID-19 Hack', '2nd Place Hack'] | ['drone', 'firebase', 'keras', 'opencv', 'python', 'swift', 'tensorflow', 'xcode'] | 20 |
9,921 | https://devpost.com/software/rona-p7tlns | COVID-19 Self Test
Rona
Rona Analytics Platform
Rona Analytics Platform
Inspiration
I saw the misinformation that was being spread mainly through social media platforms. Most of this was through chatting which seems to be something most people love doing. So I saw it would be a good idea if there could be a platform where they could clarify the same misinformation, through a chat interface.
Also, the Cabinet Secretary of Ministry of Health in Kenya, spoke on Radio and said that it cost Ksh 2500 to run a single test, which on most cases needed to be run more than once on a single sample, to confirm the accuracy. This cost is the same irregardless of whether the test turns out positive or negative.
I saw it necessary to integrate a feature that would allow identification of potential candidates for testing, therefore, reducing the cost of testing by testing the persons who are marked as highly risky.
What it does
Rona is an AI driven bot that provides COVID-19 educational content and allows users to perform a self test and assess their risk of having the COVID-19
Rona is also coupled with an advanced analytics channel tuned to provide granular risk assessment and real-time trend analysis across the country. and track the disease spread across counties in Kenya with graphs that can visualize the state and help flatten the curve by allowing several measures to be taken.
It also visualizes all the counties in Kenya which are restricted for travel within Kenya to enable truck drivers and logistic providers to plan their routes better
How I built it
I built a custom NLP algorithm to analyze user's questions and optimized it with IBM Watson, and a web crawler to search the internet for COVID-19 related news from verified news sites, which I optimized with IBM Watson Discovery
I also built an API to fetch the county level statistics from a remote daataset that I manually built by collecting data reported since the first case in Kenya.
Challenges I ran into
I encountered challenges gathering the data and building a remote dataset for the disease spread across counties. However, I searched from various News pages and also the Government's website and built the dataset.
What I learned
How to optimize custom machine learning models with IBM Watson services.
How to build a dataset from scratch and build an API to fetch the data from that dataset to the platform
Through the talks administered by the Quarantine Hackathon officials, I have learnt how to think of long term solutions that are they key drivers for sustainable innovation
What's next for Rona
Next Phase:
Rona aims to partner with organizations that may find the data we collect useful, and also partner with hospitals to allow users who find they have a high likelihood of having COVID 19, to dial in to hospitals and get online support.
Long term goals:
Rona aims to be a social entreprise that provides grabular risk assessment tools for real time trend analysis for various diseases.
Built With
google-places
ibm-cloud
ibm-watson
json
python
Try it out
Rona.co.ke
Analytics.rona.co.ke | Rona | Rona is an AI driven bot that allows users to perform a COVID-19 self test, Coupled with an analytics channel tuned to provide granular risk assessment and real-time trend analysis across the country | ['Brian Ndegwa'] | [] | ['google-places', 'ibm-cloud', 'ibm-watson', 'json', 'python'] | 21 |
9,921 | https://devpost.com/software/social-distance-monitor | supermarket
bus station
Inspiration
The world health organisation has adopted the social distance as one of the most important tools in the fight against corona virus which makes many countries to lockdown and initiate rule for social distancing. However, it is not an easy task to monitor to how much people are committed to these rules.
The project aims to find a solution for monitoring the public places and determine regions that require the authorities to take actions in order to maintain the public health.
What it does
It is a software system that is make use of any surveillance camera in order to monitor the movement of all pedestrians and make sure that they are committed to the social distancing rules. The system will be able to detect crowds and send an alert to the used in order to take action
How I built it
I used YOLOv3 to build the algorithm that detection people.
Pytorch is used to build the netword and train it.
The software can be used by:
1- Hypermarkets: in order monitor the number of people and take decisions accordingly.
2- Governments: In order to make sure that all people and entities are commited to the lockdown, or to take actions when the system detects crowded places
3- At train station: In order to prevent crowds or to temporarily lock the station.
Alot more ....
Built With
computer-vision
deep-learning
python
pytorch
yolov3
Try it out
github.com | Social distance monitor | Social distance monitor with survalliance cameras using AI and Computer vision algorithms | ['Moaaz AbdulRahman'] | [] | ['computer-vision', 'deep-learning', 'python', 'pytorch', 'yolov3'] | 22 |
9,921 | https://devpost.com/software/covmd-helping-doctors-spread-covid-19-expertise | CovMD.org
The problem
There is a dire lack of clear guidelines for doctors and the current landscape of exchange of expertise on COVID-19 is scattered. Virtual webinars and government/WHO case management protocols may not be niche enough or updated enough, especially for doctors in underdeveloped countries.
Our solution
_ CovMD is a platform with one simple goal: to connect doctors around the world to each other. _
covmd.org, a functional website built with WordPress, enables doctors to provide and receive COVID-19 expertise and support, wherever they are, whatever resources they have. From discussing academic collaboration with another expert through one-on-one private video chat to asking a question about a specific case on the forum, doctors are empowered with CovMD.
The first feature
allows doctors in need to be paired up with experienced physicians to offer individualized consultations-- personal or professional, related to COVID-19. The consultations can occur through video chat, already integrated with agora.io in the website. No two interactions between doctors are alike. Some calls may be oriented around sharing technical expertise, some may be to just talk to each other in times of need. The website provides doctors with the agency to choose and shape their experience to their preference, in a way that other medical platforms don't.
In addition
, doctors will be able to ask questions and respond to queries on the forum, and immediately search up the latest discussion on drugs and the most recent updates on vaccines or treatment. The forum will also include translated case studies specific to COVID-19 treatment. The idea is to layout quick and reliable information on the platform similarly to sites like Quora and Reddit, but specifically tailored for doctors tackling COVID-19.
What we have done during the weekend
We have developed a functional website through WordPress, collected feedback from 100+ doctors with a survey and built a solid business model.
The survey, in English, Mandarin Chinese and French, gave us particularly significant insight from doctors around the world: 45% of doctors reported a “Lack of clear guidelines”,
32% described a “Lack of expert advice on managing Covid-19 cases” and
15% “do not know where to look for expert advice”.
When asked how valuable would suggestions and stories from foreign doctors with Covid-19 experiences be, on a scale of 1 to 5, all doctors responded within 3-5, 44% of them 5 out 5.
60% of doctors stated regularly discussing COVID-19 issues and cases on online platforms, and among the 40% that did not, two-thirds were open to doing it in the future.
Interestingly, the main online platforms used by the doctors were Facebook, Whatsapp, far ahead of the main existing medical platforms, which do not provide one-to-one video chats and multilingual platform.
=> These results indicate that doctors prefer to connect on a personal basis and highlight the need for an international platform allowing doctors to provide and receive Covid-19 expertise.
Our solution’s impact on the crisis
_“The virus doesn’t care about borders.” Bill Gates, 12 April 2020. _ Our solutions to COVID-19 shouldn’t either. Doctors around the world are tending to millions of COVID-19 patients and having to deliver bad news as the death toll surpasses 200,000. Not to mention, they are dealing with a rapidly spreading virus and having to adapt their practice day-to-day to best treat patients. As per the abovementioned survey results and the doctors and mentors we have personally spoken to, our solution has the potential to bridge the expertise gap by providing doctors around the world with a novel platform empowering them in this global fight. CovMD is a platform where they can call, consult cases on forums and attend webinars with other doctors more easily.
Our next steps to continue the project
1: Pilot testing
2: Expanding user base and refining platform
3: Expansion of new features
1: Pilot testing: We are starting the testing of the website with doctors who answered the survey. We have reached out to Ghana Medical Association to seek opportunities to collaborate with them. We are also participating in MIT COVID-19 Challenge in Africa to look for potential partners there. We will also be contacting other medical associations with our contacts to find opportunities for further pilot test.
2: Expanding user base and refining platform : We will start hosting Covid-19 webinars with Q&A, with top medical experts, and contact MDs through partner channels (:FB groups, medical associations, MIT/EU networks)
3: Expansion of new features: Building upon a growing pool of doctors and sufficient funding, we will set-up an intelligent matchmaking algorithm between doctors in need and expert physicians, acknowledging the varying needs across resources and countries.
The value of our solution(s) after the crisis
Post-COVID, this platform can leverage on the existing user network of doctors and hospitals and operate as a platform for clinicians to apply for fellowship and exchange programmes across many hospitals in the world. Currently this process is fragmented and both the hospitals and doctors can benefit from such a platform which provides information on application requirement, deadline and allow clinicians to submit all applications and request references at one go. The Covid-tried match-making algorithm, fine-tuned for Covid-19 issues, may also become relevant to deal with different sorts of health challenges requiring global, coordinated responses at the level of doctors.
The URL to the prototype:
www.covmd.org
The URL to the pitchvideo:
https://youtu.be/3Tv9wxWOAd4
Overall
: CovMD aims at connecting doctors from around the world together in a single platform.
Our purpose is to enable doctors to provide and receive COVID-19 expertise and support, wherever they are, whatever resources they have: from discussing academic collaboration with another expert through one-on-one private video chat to asking a question about a specific case on the forum. We are working every day to make this humble website a warm place where every doctor can feel heard, supported, and empowered in this common, global fight against COVID-19.
Built With
wordpress
Try it out
www.covmd.org | CovMD | Spread expertise, not the virus - a platform for doctors to provide educational resources and mentorship for each other | ['Timing Liu', 'Max Lehman', 'Chenhe Gu'] | [] | ['wordpress'] | 23 |
9,921 | https://devpost.com/software/digital-trends-for-industry | digital trends for industry
Built With
powerpoint | Digital Trends for Industry | digital trends for industry | ['Yousra Aboulatta'] | [] | ['powerpoint'] | 24 |
9,921 | https://devpost.com/software/new-education-system | Inspiration
I got inspired to create this idea because of the lack of education nowadays, we already know that there's a lot of students in universities who don't like their fields and they were forced to choose their faculty and their fields because of their rate in the third year at the high school, therefore, they got depressed and they started to be as minions for the curriculums which they hated and as a result of all these they start to restrict their thoughts and feel hopeless because they know that their minds would be fruitful in another field, then, when they graduate from their faculty they divide into two groups, the first one always seek to shift their careers because they already hate It, the other always try to adapt with the gruesome fact and work in routine without thriving, so I was thinking why we should live all these awful situations without any change, and from this point, I started to search for a solution, at first I was thinking about how to modify our ordinary method, it took me a lot of time to make it fit what I hope but I revealed many gaping holes in our ordinary method make it enable to be modified. From here, i started to find another solution which will be illustrated below.
What it does
It's an e-learning method depends on self-paced, i create this method to get rid of all the badness in the first paragraph above, this new way will provide all students with their needs, the method will make anyone master any field in his self-paced, so you aren't restricted with a faculty or a method, the idea is to deal with the ministry of high education to make a site which we need to know if i want to master a field what should i study, for example, if i want to master mathematics i should go to the site and enter the mathematics field and the site will inform me with the courses that i need to master this field.
Then we should go to a platform to study the desired courses and here the ministry will deal with some of the educational platforms to provide the student with the desired courses which need essential fees to join but the student isn't restricted with these courses he can take the same courses from other platforms.
The ministry will make periodic exams that we need to certify our study to take a certified certification which allows us to work.
There's a lot of benefits for all starting from the students to the ministry and the platforms which can market for its courses besides the ministry's courses.
This method will achieve one of SDGs "High-Quality Education" and help us to continue the educational process in these troubling circumstances safely and in high quality.
How I built it
I didn't build anything because it's a proposal plan, so all we need is just permission from the ministry to apply this idea in reality.
Challenges I ran into
I run into some challenges like how can I show my idea for a prestigious person who has the power to illustrate this idea for the ministry because of that I started to ignore it because I know that I'll not have this power nowadays, nevertheless, I kept it my mind and the recent circumstances has revived it again as we all know all universities seeking for online-learning because of that I got inspired again and saw this hackathon as a chance to show it in real.
Accomplishments that I'm proud of
Till now I didn't make any accomplishment which I feel proud of it ؟ is to take permission and apply it in reality.
What I learned
I have learned to find solutions for the public that might make an essential impact on the society.
What's next for New Education System
The upcoming thing is to take permission and apply it in reality. | New Education System | It all about e-learning but in self-paced way, so you don't follow a specific organization | ['Mohammed Hussein'] | [] | [] | 25 |
9,921 | https://devpost.com/software/masked-ai-masks-detection-and-recognition | Platform Snapshot
Input Video
Model Processing
Model Processing
Output Video Saved
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Output Video Snapshot
Inspiration
The total number of Coronavirus cases is 5,104,902 worldwide (Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and taking preventive measures is the only option to flatten the curve. Face Masks Are Crucial Now in the Battle Against COVID-19 to stop community-based transmission. But we are humans and lazy by nature. We are not used to wear masks when we go out in public places. One of the biggest challenges is “People not wearing masks at public places and violating the order issued by the government or local administration.” That is the main reason, we built this solution to monitor people in public places by Drones, CCTVs, IP cameras, etc, and detect people with or without face masks. Police and officials are working day and night but manual surveillance is not enough to identify people who are violating rules & regulations. Our objective was to create a solution that provides less human-based surveillance to detect people who are not using masks in public places. An automated AI system can reduce the manual investigations.
What it does
Masked AI is a real-time video analytics solution for human surveillance and face mask identification. Our main feature is to identify people with masks that are advised by the government. Our solution is easy to deploy in Drones and CCTVs to “see that really matters” in this pandemic situation of the Novel Coronavirus. It has the following features:
1. Human Detection
2. Face Masks Identification (N95, Surgical, and Cloth-based Masks)
3. Identify human with or without mask in real-time
4. Count people each second of the frame
5. Generate alarm to the local authority if not using a mask (Soon in video demo)
It runs entirely on the cloud and does detection in real-time with analysis using graphs.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. JavaScript for the frontend features
5. Embedded technologies
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 1000 good quality images of multiple classes of face masks (N95, Surgical, Clothe-based masks). We then performed data-preprocessing and labeled all the images using labeling tools and generated PASCAL VOC and JSON after the labeling.
2. Model Preparation:
We used one of the famous deep learning-based object detection algorithm “YOLO V-3” for our task. Using darknet and Yolo v-3, we trained the model from scratch on 16GB RAM and Tesla K80 powered GPU machine. It took 10 hours to train the model. We saved the model for deploying our solution to the various platforms.
3. Deployment:
After training the model, we built the frontend which is totally client-based using JavaScript and microservice “Flask”. Rather than saving the input videos to our server, we are sending our AI to the client’s place and using Microsoft Azure for the deployment. We are having on-premise and cloud solutions prepared. At the moment, we are on a trail so we can’t provide the link URL.
After building the AI part and frontend, We integrated our solution to the IP and CCTV cameras available in our house and checked the performance of our solution. Our solution works in real-time on video footage with very good accuracy and performance.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself. For that reason, we can’t go outside the home for the hardware and embedded parts. We are working virtually to build innovative solutions but as of now, we are having very limited resources. We can’t go outside to buy hardware components or IP & CCTV cameras. One more challenge we faced was that we were not able to validate our solution with drones in the early days due to the lockdown but after taking permission from the officials that problem was not a deal anymore.
Accomplishments that we're proud of
Good work brings the appreciation and recognition. We have submitted our research paper in several conferences and international journals (Waiting for the publication). After developing the basic proof-of-concept, We went on to the local government officials and submitted our proposal for a trial to check our solution for better surveillance because the lockdown is near to be lifted. Our team is also participating in several hackathons and tech event virtually to showcase our work.
What we learned
Learning is a continuous process. We mainly work with the AI domain and not with the Drones. The most important thing about this project was “Learning new things”. We learned how to integrate “Masked AI” into Drones and deploy our solution to the cloud. We added embedded skills in our profile and now exploring more features on that part. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for Masked AI: Masks Detection and Recognition
We are looking forward to collaborating with local administrative and the government to integrate our solution for drone-based surveillance (that’s currently in trend to monitor internal areas of the cities). Parallel, The improvement of model is the main priority and we are adding “Action Recognition” and “Object Detection” features in our existing solution for even robust and better solution so decision-makers can make ethical decisions as because surveillance using Deep Learning algorithms are always risky (bias and error in judgments).
Built With
azure
darknet
flask
google-cloud
javascript
nvidia
opencv
python
tensorflow
twilio
yolo | Masked AI: AI Solution for Face Mask Identification | Masked AI is a cloud-based AI solution for real-time surveillance that keeps an eye on the human who violates the rule by not using face masks in public places. | [] | [] | ['azure', 'darknet', 'flask', 'google-cloud', 'javascript', 'nvidia', 'opencv', 'python', 'tensorflow', 'twilio', 'yolo'] | 26 |
9,921 | https://devpost.com/software/covnatic-covid-19-ai-diagnosis-platform | Landing Page
Login Page
Segmentation of Infected Areas in a CT Scan
Check Suspects using Unique Identification Number (New Suspect)
Check Suspects using Unique Identification Number (Old Suspect)
Suspect Data Entry
COVID-19 Suspect Detector
Upload Chest X-ray
Result: COVID-19 Negative
Upload CT Scan
Result: Suspected COVID-19
Realtime Dashboard
Realtime Dashboard
Realtime Dashboard
View all the Suspects (Keep and track the progress of suspects)
Suspect Details View
Automated Segmentation of the infected areas inside CT Scans caused by Novel Coronavirus
Process flow of locating the affected areas
U-net (VGG weights) architecture for locating the affected areas
Segmentation Results
Detected COVID-19 Positive
Detected Normal
Detected COVID-19 Positive
Detected COVID-19 Positive
GIF
Located infected areas inside lungs caused by the Novel Coronavirus
Endorsement from Govt. Of Telengana, Hyderabad, India
Endorsement from Govt. Of Telengana, Hyderabad, India
Generate Report: COVID-19 Possibility
Generate Report: Normal Case
Generated PDF Report
Inspiration
The total number of Coronavirus cases is
2,661,506 worldwide
(Source: World o Meters). The cases are increasing day by day and the curve is not ready to flatten, that’s really sad!! Right now the virus is in the community-transmission stage and rapid testing is the only option to battle with the virus. McMarvin took this opportunity as a challenge and built AI Solution to provide a tool to our doctors. McMarvin is a DeepTech startup in medical artificial intelligence using AI technologies to develop tools for better patient care, quality control, health management, and scientific research.
There is a current epidemic in the world due to the Novel Coronavirus and here
there are limited testing kits for RT-PCR and Lab testing
. There have been reports that kits are showing variations in their results and false positives are heavily increasing.
Early detection using Chest CT can be an alternative to detect the COVID-19 suspects.
For this reason, our team worked day and night to develop an application which can help radiologist and doctors by automatically detect and locate the infected areas inside the lungs using medical scan i.e. chest CT scans.
The inspirations are as below:
1. Limited kit-based testings due to limited resources
2. RT-PCR is not as much as accurate in many countries (recently in India)
3. RT-PCR test can’t exactly locate the infections inside the lungs
AI-based medical imaging screening assessment is seen as one of the promising techniques that might lift some of the heavyweights of the doctors’ shoulders.
What it does
Our COVID-19 AI diagnosis platform is a fully secured cloud based application to detect COVID-19 patients using chest X-ray and CT Scans. Our solution has a centralized Database (like a mini-EHR) for Corona suspects and patients. Each and every record will be saved in the database (hospital wise).
Following are the features of our product:
Artificial Intelligence to screen suspects using CT Scans and Chest X-Rays.
AI-based detection and
segmentation & localization of infected areas inside the lungs
in chest CT.
Smart Analytics Dashboard
(Hospital Wise) to view all the updated screening details.
Centralized database (only for COVID-19 suspects) to
keep the record of suspects and track their progress
after every time they get screened.
PDF Reports,
DICOM Supports
, Guidelines, Documentation, Customer Support, etc.
Fully secured platform
(Both On-Premise and Cloud)
with the privacy policy under healthcare data guidelines.
Get Report within Seconds
Our main objective is to provide a research-oriented tool to alleviate the pressure from doctors and assist them using AI-enabled smart analytics platform so they can
“SAVE TIME”
and
“SAVE LIVES”
in the critical stages (Stage-3 or 4).
Followings are the benefits:
1. Real-world data on risks and benefits:
The use of routinely collected data from suspect/patient allows assessment of the benefits and risks of different medical treatments, as well as the relative effectiveness of medicines in the real world.
2. Studies can be carried out quickly:
Studies based on real-world data (RWD) are faster to conduct than randomized controlled trials (RCTs). The Novel Coronavirus infected patients’ data will help in the research and upcoming such outbreak in the future.
3. Speed and Time:
One of the major advantages of the AI-system is speed. More conventional methods can take longer to process due to the increase in demand. However, with the AI application, radiologists can identify and prioritize the suspects.
How we built it
Our solution is built using the following major technologies:
1. Deep Learning and Computer Vision
2. Cloud Services (Azure in this case)
3. Microservices (Flask in this case)
4. DESKTOP GUIs like Tkinter
5. Docker and Kubernetes
6. JavaScript for the frontend features
7. DICOM APIs
I will be breaking the complete solution into the following steps:
1. Data Preparation:
We collected more than 2000 medical scans i.e. chest CT and X-rays of 500+ COVID-19 suspects around the European countries and from open source radiology data platform. We then performed validation and labeling of CT findings with the help of advisors and domain experts who are doctors with 20+ experience. You can get more information in team section on our site. After carefully data-preprocessing and labeling, we moved to model preparation.
2. Model Development:
We built several algorithms for testing our model. We started with CNN for classifier and checked the score in different metrics because creating a COVID-19 classifier is not an easy task because of variations that can cause bias while giving the results. We then used U-net for segmentation and got a very impressive accuracy and got a good IoU metrics score. For the detection of COVID-19 suspects, we have used a CNN architecture and for segmentation we have used U-net architecture. We have achieved 94% accuracy on training dataset and 89.4% on test data. For false positive and other metrics, please go through our files.
3. Deployment:
After training the model and validating with our doctors, we prepared our solutions in two different formats i.e. cloud-based solution and on-premise solution. We are using EC-2 instance on AWS for our cloud-based solution.
Our platform will only help and not replace the healthcare professionals so they can make quick decisions in critical situations.
Challenges we ran into
There are always a few challenges when you innovate something new. The biggest challenge is “The Novel Coronavirus” itself.
One of the challenge is “Validated data” from different demographics and CT machines.
Due to the lockdown in the country, we are not able to meet and discuss it with several other radiologists. We are working virtually to build innovative solutions but as of now, we are having very limited resources.
Accomplishments that we're proud of
We are in regular touch with the State Government (Telangana, Hyderabad Government). Our team presented the project to the Health Minister Office and helping them in stage-3 and 4.
Following accomplishments we are proud of:
1. 1 Patent (IP) filled
2. 2 research paper
3. Partnership with several startups
4. In touch with several doctors who are working with COVID-19 patients. Also discussing with Research Institutes for R&D
What we learned
Learning is a continuous process. Our team learnt
"the art of working in lockdown"
. We worked virtually to develop this application to help our government and people. The other learning part was to take our proof of concept to the local administration for trails. All these “Government Procedures” like writing Research Proposal, Meeting with the Officials, etc was for the first time and we learned several protocols to work with the government.
What's next for M-VIC19: McMarvin Vision Imaging for COVID19
Our research is still going on and our solution is now endorsed by
the Health Ministry of Telangana
. We have presented our project to
the government of Telangana for a clinical trail
. So the next thing is that we are looking for trail with hospitals and research Institutes. On the solution side, we are adding more labeled data under the supervision of Doctors who are working with COVID-19 patients in India. Features like
Bio-metric verification, Trigger mechanism to send notification to patients and command room
, etc are under consideration. There is always scope of improvement and AI is the technology which learns on top of data. Overall, we are dedicated to take this solution into real world production for our doctors or CT and X-rays manufacturers so they can use it to fight with the deadly virus.
Built With
amazon-web-services
flask
google-cloud
javascript
keras
nvidia
opencv
python
sqlite
tensorflow
Try it out
m-vic19.com | M-VIC19: McMarvin Vision Imaging for COVID19 | M-VIC19 is an AI Diagnosis platform is to help hospitals screen suspects and automatically locate the infected areas inside the lungs caused by the Novel Coronavirus using chest radiographs. | [] | ['1st Place Overall Winners', 'Third Place - Donation to cause or non-profit organization involved in fighting the COVID crisis'] | ['amazon-web-services', 'flask', 'google-cloud', 'javascript', 'keras', 'nvidia', 'opencv', 'python', 'sqlite', 'tensorflow'] | 27 |
9,921 | https://devpost.com/software/sechat-f3k1u9 | we got the inspiration from the people around us during this quarantine, in which most people wanted to learn new skills and enhance their skills in certain topics. So we started to think that it could be beneficial to create an online platform where people could exchange their skills from home using video calls from the app. For example one user is good at coding but he needs to learn drawing and another user is good at drawing and want to learn coding, the application will match them so they start to teach and learn at the same time without any cost. The application will also have a place where you can get an honest constructive feedback on your work. For example if the user is playing guitar and wants to know if he is doing it well or need improvement in certain notes, he could upload a video of himself playing guitar and ask for opinions from people who has experience in guitar.
The application solve the problem of people who want to take courses in certain fields but doesn't have the money or doesn't have time. It also helps people who have good experience in some topic but need to know more in that topic from a more experienced user.
We did surveys to test how people would perceive it, how could it help them and if they could use such a platform to learn and teach at the same time.
What is next for us is that we will start creating the prototype and release it in the app/play store to get feedback from customers and then we will launch our application afterwards. | sechat | the idea is an application to exchange skills between users and give feedback. A user opens sechat to learn a certain skill from another user and in exchange he should teach him a skill as well | ['sara hesham', 'Hassan Hanbel'] | [] | [] | 28 |
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