T-Mobile
Wireless Broadband Service Quality Prediction App
This student team worked to design and test a system comprised of a simple, customer "do-it-yourself" tool embodied as an Android app. This app reads low and FDD mid-band signal quality being experienced in the home and, using a machine learning based model, predicts service quality for the higher TDD mid-bands. Through this, the app can tell the internet speed the customer can expect from the T-Mobile Home Device before subscribing to it.
Faculty Adviser(s)
Anthony Goodson, Electrical & Computer Engineering
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