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.
They explicitly went into the advantages over cameras:
So perhaps a building takes a picture of everyone as they come in the front door and also establishes a ‘WhoFi’ profile for that person. They could keep track of their movement through the building while maintaining an actionable correlation to a photo.