We were inspired by one of our group members who had relatives living in India. They recounted the problems Indians are facing currently with regards to the COVID-19. This main problem was a lack of information and a growing amount of misinformation which is what our idea aims to alleviate.
What it does
Out project has two main functions. The first is that it helps users find nearby hospitals, vaccination centers, and testing centers. We gathered the locations of all of these facilities through multiple databases, and ideally, we would use crowdsourcing to find all the additional information on the facilities like the quality and speed of the facilities. In addition, we would ideally have these facilities join our platform so they could provide real-time information on their facilities like information on capacity. The second function of our project was to utilize the ML model we developed to determine if a COVID-related news article was fake or real. We utilized several features common both in real and fake news articles to create the model. Users can input the title of their article and one or two paragraphs from their article, and our ML model will attempt to determine if the article is real or not.
How we built it
We constructed the frontend using HTML and CSS. The ML model was constructed using python and the integration of scikit-learn. Finally, for the backend, we utilized Flask, and integrated the google maps API to create the map with all of the facility locations.
Challenges we ran into
Our main issue was connecting the ML model to the website. In addition to this, we had issues with simply creating the project in the time allotted to us since we were in a different time zone.
What we were proud of
We were proud of even completing this project because it was our first Hackathon. Even though this project was not our best work, we still put in a lot of work to make it as good as possible.
What's next for Save India
Next would be to reach out to the hospitals and other facilities in India, as well as begin the process of crowdsourcing.
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