I was laying in bed at 4am on a Saturday morning, trying to come up with any way I could help my good friend who owns 70+ restaurants. That’s when I had an epiphany, how do we know the restaurants aren’t safe but the grocery stores are? How do we flatten the curve? The answer was simple, identify earlier and self-quarantine before you're contagious. Then, it was as simple as how can we predict who may have COVID-19, before they have symptoms. You can’t get sick, if you aren’t exposed.
What it does
It is a source of timely and geographically relevant public health and public safety advisories to keep people about the coronavirus and pandemic response. Although it would ultimately depend on the preferences of the issuing authority, I planned to give an exposure score and show it right in the app along with individual advisories, if the algorithm determines that you should be self-quarantined or get tested.
How I built it
iOS and Android clients push anonymous movement to an AWS Lamda function into a DynamoDB, where data scientists and AI take over.
Challenges I ran into
The only challenge thus far is getting the concept in front of the right person.
Accomplishments that I'm proud of
Proud of my Stature team that pivoted to produce the prototype with blinding speed. Proud to be associated with our beloved partners, Blueforce Development, Cadence, and QueBIT.
What I learned
I’ve learned that no matter how good the idea, you need the right people to get the word out.
What's next for COVID-19 Exposure App
Once we get deployed to the masses, the data scientists will start analyzing the data to collect data points that are clinically valuable, such as pinpointing the period of being contagious in the lifecycle of the virus.
Try It out
ai, amazon-dynamodb, amazon-web-services, android, dynamo, ios, machine-learning