Humans can be tracked with unique 'fingerprint' based on how their bodies block Wi-Fi signals

The Sapienza computer scientists say Wi-Fi signals offer superior surveillance potential compared to cameras because they're not affected by light conditions, can penetrate walls and other obstacles, and they're more privacy-preserving than visual images.

[…] The Rome-based researchers who proposed WhoFi claim their technique makes accurate matches on the public NTU-Fi dataset up to 95.5 percent of the time when the deep neural network uses the transformer encoding architecture.