FocusFlow - BU Study Spots

Inspiration

In a university as prestigious as BU, students have rigorous standards when it comes to academics. This means thousands of hours invested in studying in order to maintain our grades. For all students, comfort is key in order to study well - we need a quiet, aesthetically pleasing and clean environment. However, this is not always possible - every day, students pile into the most popular study spots, leaving them crowded, noisy, and inhospitable for an efficient cram session.

What it does

To fix this, we created FocusFlow. The perfect tool to check what spots are available and comfortable on the go.

How we built it

We coded the backend by using python to calculate distance in miles using longitude and latitude, normalized features for comparability purposes, and adjusted the weights of the rating and location features depending on the number of ratings of a study spot and a specific cutoff distance threshold respectively. The frontend was designed on Figma, then built by vibecoding in React using Claude and debugging. We connected the frontend to the server by vibe coding the two together, allowing the points on the frontend to take the calculated algorithm and ranking the locations near the user, displaying on the interactive.

Challenges we ran into

Finding specific data pertaining to foot traffic in physical buildings at specific times in the Boston area was difficult, so we simulated this using data with similar features. D

Accomplishments that we're proud of

Without a lot of experience, it was challenging to implement an algorithm to choose what location to pick for the user as well as being able to integrate a map into our project. We were proud of finding ethically sourced data as well as continuing to work through roadblocks successfully as a team.

What we learned

As this was all of our first time taking part in a hackathon, we learned how to leverage our different skillsets to work together efficiently. We all learned how to communicate with a team better.

What's next for FocusFlow: BU Study Spots

There are features we want to implement to make a greater impact with FocusFlow such as improve user ratings to be more accurate by timing them out in an hour. Along with this we would implement outlier detection which would weigh down spam and malicious reviews automatically. We mainly also aim to work with the BU IT team to get data from local wifi servers to check how crowded a potential study spot is without compromising the privacy of our customers.