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.

    • realitista@lemmus.org
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      18 hours ago

      Well they can identify you are the same person but not your identity… So it’s like a disenbodied fingerprint.

      I suppose they could potentially make some database and train an AI on it someday to match to actual identities, but usefulness would be pretty limited at only 95% accuracy. That’s a false reading 1/20 times, so I suspect it would fail bigly to accurately recognize people from large data sets.

      • Warehouse@lemmy.ca
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        16 hours ago

        That’s a false reading 1/20 times

        And when has something like that ever stopped anyone?