Inspiration: Our Teammate Will recently overcame his nicotine addiction and thought this could help people in a similar situation
What it does: Using multiple health metrics, RelApps can detect a potential relapse. If the user is deemed high risk, then the application will automatically inform emergency contacts about the same via email and text.
How we built it we built this using: HTML5/CSS3, Bootstrap, PHP, Python, SQL, and Twilio API
Challenges we ran into: Working with multiple versions of python along with trying inter-language communication. Receiving accurate health data is a challenge.
Accomplishments that we're proud of: making this application work almost exactly as desired
What's next for RelApps: We aim to work research facilities and hospitals in making our algorithm to detect relapse more accurate. We hope to promote a working version of this application to college administrators, health practitioners.
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