Built by MIT 6.9000 Team 2.
Andy, Sydney, Ann
Jonatan, Justin, Annie
Ann, Sydney
Tori
Annie, Jonatan, Sydney, Andy
Cole
Justin, Cole
This project was built for MIT 6.9000 (Spring 2026). The purpose of the system is to understand the local heat experience on different parts of the MIT campus.
Brian Goldberg’s presentation from Lecture 2 is available to review.
An end-to-end system: devices → backend → database → map UI
Low-friction deployment • clear UX • reliable data ingest
* → *** indicates level of importance.
We treated this as a sensing → interpretation → decision problem. A small fleet of devices collects local conditions, and the dashboard turns that into a map you can act on (where to avoid, where to go), with time controls to compare “now” vs earlier.
Distributed readings across campus areas, updated continuously.
Campus is divided into polygons (“sectors”) so we can aggregate and compare regions.
Map-first UI with relative hot/cool cues and drill-down on click.
Admin workflow to keep the fleet healthy and the data trustworthy.
Technical details (API layout, DB schema, seeding, etc.) live in the linked docs below so this page stays readable.
Add links here for your writeup and presentation. These can point to Figma, PDFs, or repo files. There is also a FAQ that might be useful.