The world we live in has changed dramatically amidst the COVID-19 outbreak. Although some of us are safe at home with the proper equipment, a large portion of the population does not have access to essentials. In analyzing the issue, we realized the immunocompromised currently had no access to essentials as they could not simply leave their houses to go to a grocery store. We decided to provide a solution to this problem by creating a website in which we could allow users to make virtual requests for items, such as toilet paper or hand sanitizer, and then enable volunteers to accept these requests to donate supplies to them. As there is no preexisting platform that allows for direct pairings between users and volunteer deliverers, we believe this is the perfect solution to help those most impacted by COVID-19.
What it does
CovAid is a web application that connects volunteers to those in need during the COVID-19 outbreak using AI-driven intelligence. The website connects at-risk users with volunteers willing to donate necessities. Users can make requests for items to the website and volunteers can respond to those requests. These pairings are created efficiently with a machine learning algorithm that takes into account various factors such as the distance between the user and the volunteer.
How we built it
Challenges we ran into
We faced numerous challenges when it came to properly communicating with Flask view and the various HTML templates. Since CovAid is a dynamic site form data had to be sent back and forth between the files and stored in a database. Using a database was something new to all of us and understanding how to integrate it for our needs was a major roadblock for a while. Another major challenge was implementing our machine learning sorting algorithm with our Flask and HTML to sort the requests for each volunteer, since we had to learn how to get live user data to enter into the model.
Accomplishments that we're proud of
We are proud of how we could efficiently push out a website while allowing everyone on our team to contribute equally. After beginning with our entire team working together to create the basic layout of our website, we split up into two teams. Shrey and Atin worked on the front-end and back-end of the website while Anirudh and Aarav worked on the machine learning aspect of the project. We also learned various CS skills while also helping our community at the same time. In addition, we are also pleased that we have created another scenario that AI can help ease our lives. We are excited to see how our project will be able to create opportunities for other people to make a positive impact on their surroundings.
What we learned
In developing CovAid, aside from exploring new software such as Bootstrap and Flask, we fully understood the broader impacts of our project — that any simple act of kindness can be influential, especially to those that are impacted the most from issues like these.
What's next for CovAid
In order to create a real difference in our community we hope for CovAid to be more widespread and have a larger impact on the world. We also want to implement a system in which users are able to be further interconnected. Our vision is that through our product everyone will have access to essentials and will stay safe as our world continues to change from COVID-19.
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