Wi-Find

When you get your T-Mobile home internet router, it’s hard to find a spot easily where you get good internet, even in small/enclosed locations. Finding the best spot usually takes a lot of time and sometimes can be really bad and it takes a lot of moving around and you won't really know visually unless you have to run random speed tests and guess where it performs the best.

We wanted to build a smarter way to find the best router placement automatically — something visual, intelligent, and user-friendly. That’s where Wi-Find comes in.

At first, we weren’t sure how to collect and process real-time network data effectively. We experimented with tools for measuring signal strength, latency, and Mbps speeds, but getting them to sync live through a Raspberry Pi was a big hurdle. Then came the visualization challenge: how do we turn raw numbers into something people can actually understand at a glance?

We solved this by integrating AI-driven analytics with a heatmap visualization system. Using a calibration process, the user walks through corners of the room, allowing our system to scan and map Wi-Fi latency in different areas. The result? A colorful, real-time heatmap that shows exactly where your internet is strongest or weakest — no guessing, no constant router shuffling.

Our biggest learning moment was realizing how much data can change just by moving a few feet. It taught us how dynamic Wi-Fi environments really are and how valuable AI can be in making sense of it all.

By the end of the hackathon, we had built a working prototype that not only measured performance but also visually guided users to the perfect router placement. What started as a small frustration turned into a powerful tool to make home networking smarter, faster, and easier.