Inspiration

The inspiration for this project came from the fact that many times elderly people will take readings for their health and might have readings that indicate a possible medical emergency, but they might not know.

What it does

Using a medical machine learning python module, we created a web app that allows people to enter their medical data and contact the appropriate services if there are signs of an emergency.

How we built

We built it by using a medical machine learning module call MedicareAI and then used flask and sqlite3 to create a website and store information.

Challenges we ran into

First, the flask would not function on our google console server We had to get the components to communicate properly (front-end HTML, back-end python using MedicareAI for machine learning, python using flask connecting them, and SQL storing the data). We were also unable to get the Dragonboard to work properly with the temperature sensor.

Accomplishments that we're proud of

We are really proud of getting the machine learning and the flask MySQL integration working. We also really like the UI that we used.

What we learned

We learned how to use flask, sqlite3, and how to integrate the websites together.

What's next for MedAlert

The goal is to develop this into a actual product and have this deployed for actual patients with legitimate data.

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