betterT

Inspiration

Inspiration was our daily interaction with T, especially with two stops: Northeastern and Ruggles.

What it does

The goal was for betterT to render yesterday's T data, and then ask for user input. Then it generates the user's ideal based on the weights from the UI slider.

How we built it

We used Next.JS as our project framework, with React and MaterialUI for the front end, Tableau for visualization, and the MBTA v3 API as our data source.

Challenges we ran into

Some of our challenges included importing data into Tableau, and succinctly presenting weighted possibilities to the user.

Accomplishments that we're proud of

UI designed to match the MBTA design philosophy!

What we learned

How to represent temporal and spatial data in Tableau, how to link APIs to our website, and how to use dynamic programming to figure out optimal weighted scheduling.