Let's consider the story of Chris. He is still under lockdown and he is worried about his health. Currently he is not aware of the risky areas surrounding him. So he cannot leave his home to visit the local grocery store (which he prefers to buy from over online stores) without panicking. Also he fears he might take a route through a region infected with the virus which can affect him as well. And even if he reaches the store safely, he might be faced with a crowd which doesn’t maintain social distancing; and even if they do so, they all come at the same time leading to long queues. Even after all this, there is still a chance that he might be affected but asymptomatic and he might further infect others as he might be unaware of whether he had been in contact with anyone before.
What it does
COVID-Oversight tries to mitigate the above problems with a one-stop solution for visualizing local risky areas, finding safe stores and safer routes for visiting them, creating systematic queues for reducing delays and a case reporting mechanism for leveraging crowd-sourced data to map the crisis and protect one and all
How I built it
Here maps, Twilio API, IBM Cloudant, IBM Cloud Foundry, Postman
Accomplishments that I'm proud of
- Completed the hack in under 24 hours
- Created an end-to-end communication, reporting, and verification system
What I learned
- Apllication of Twilio and Postman
- Cloud hosting
What's next for COVID-Oversight
● Integrate chatbot inside the web app ● Use IBM Watson API for further diagnosis on chatbot ● Use IBM Watson Studio to design a forecasting algorithm for better queue management and COVID spread ● Use Here Maps geofencing API and Twilio Notify API to alert users when they enter risky areas
Log in or sign up for Devpost to join the conversation.