Inspiration
When we saw all the health and wellness APIs and the challenges to help students improve their daily lives, I had an idea to fill in gaps where most wellness apps fall short. Having used wellness apps before, most of them are good at tracking, but don't do much to recommend changes. That's where BrightBrain comes in.
What it does
BrightBrain is a web application that allows a user to create an account, enter factors from their daily life like exercise, food, water, sleep, and some automatically scraped info like AccuWeather weather data, and find correlations to some results in their daily life, like their stress levels, sleep, athletic performance, and grades. When it finds strong correlations between some factor and result, it will recommend to the user different ideas and actions they can take, depending on if the correlation was positive or negative.
How we built it
BrightBrain runs as a web application in HTML/CSS and piped into a Django/Python backend server run as an AWS EC2 instance. The site allows the user to enter data from their daily lives which is stored in a SQLite database, thereafter when the user logs in, the server calculates correlations in the past week's activities to metrics we gathered via user input and Canvas score results and processed using NumPy's correlation() function. Results are then displayed back to the user on our site when they navigate back to their dashboard. In the future, more features will be added such as graphs and data visualisation for the user to understand their performance against our metrics, recommendations based on long term performance, and other lifestyle improvements.
Challenges we ran into
The main challenge was a lack of experience on the team. We had one experienced programmer and four brand new programmers. So the project was extremely ambitious compared to the timeframe given and the skill of the team. So many backend functions were not fully implemented despite the architecture being designed.
Accomplishments that we're proud of
Our two newer front end web designers created a very elegant interface for the site despite being extremely new to web design and HTML/CSS. On the backend, the algorithm and architecture behind the idea is very solid and just needs time to be implemented, and would have been possible with more experienced coders.
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