MIT trains AI to track people’s movements through walls

In 2013, an MIT team found a way to see through walls using Wi-Fi radio signals, and in 2015 the technology was advanced enough to distinguish and track individuals. Now, led by Dina Katabi from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), the team has hooked the latest version, called RF-Pose, to an artificial intelligence (AI) neural network as a way to teach it to deduce a person’s postures and movements even when completely hidden.

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