CovSupply

Inspiration

After witnessing in the recent news, pictures of an exhausted medical staff, we started to set our complaints about social distancing aside, and started to focus on the issue at hand. TShortages have gotten so bad, that staff and support facilities have had to reuse supplies such as surgical masks, inducing severe health hazards.

What it does

This is a system that allows the public, which includes communities and organizations, to see the current resources, demands, and specific donations at a hospital.

How I built it

We used a Keras based recurrent LSTM model and Google API’s for the fact checking bot. This model was incorporated into our backend Firebase and Flask application, to dynamically update user’s profiles in real time.

Challenges I ran into

Some challenges we ran into when developing the website was finding a way to host our website. Previously, when creating websites, we only needed a front-tend so hosting on GitHub pages was plausible.

Accomplishments that I'm proud of

Being able to integrate our account system with firebase and updating information on our maps in real-time.

What I learned

We learned how to effectively integrate back-end techniques, such as Flask, Firebase, and Keras, into a dynamic front-end that is based on real-time user data and input.

What's next for CoronaNet

For our Fact-Checking algorithm, we want to implement an Azure Web Scraper that returns better results for our algorithm.