Inspiration

There are people dying all over the world - pretty big motivation. Helping elderly find their way through COVID-19 Pandemic by avoiding infected and crowded locations. We can help each other by being good neighbors and reporting cases for the community.

What it does

With daily COVID-19 death tolls higher than ever, a major obstacle to recovery is the lack of information. Social distancing is hard when you don’t even know which locations have a high density of people, or which places have had infected visitors.

Our goal is to fill this lack of information by alerting users in real time to locations with confirmed cases, so that they can avoid them. This allows users to make a conscious choice to avoid certain locations, stopping contact with infections in the first place. Additionally, we use the Besttime API to forecast the safest time to visit a store days in advance by statistically analyzing trends in visitor count. These predictions allow users to avoid foot traffic in stores - a breeding ground for COVID.

How I built it

This was built in two parts. The iOS app was written in Swift, and the main frameworks used were Core Location, Radar, and Firebase. The database used to store the data was Cloud Firestore, while the UI elements were from MapKit and UIKit. The Firebase queries were done in a background thread to avoid UI lag. We made GPX files on XCode to simulate location and test our app features. We used SwiftUI to display the dashboard of predictions for various store foot traffic. The prediction was based on data from the Besttime API

Challenges I ran into

Location tracking with live firebase updates was difficult since the multithreading was complex. We had to sort out the UI vs background thread issue. Also, we had a tough time getting SwiftUI set up properly since this was our first main project with it.

Accomplishments that I'm proud of

The UI looks pretty solid in our opinion and there are a bunch of useful features on this app. Even if only one person is a good samaritan neighbor and reports a case of COVID, everyone in the area will be able to avoid that location for the incubation period. We're just really happy with coming up with the entire idea from scratch and converting it into a finished product.

What I learned

We experimented a lot with swiftui, which will help in future hackathons. We also used multiple API's (Radar, Besttime), which we can add to our toolkit in the future.

What's next for Radius

We're trying to include advanced machine learning algorithms to make our store population prediction even more accurate

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