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.
Probably not.
This kind of thing relies on the fact that the emitter and environments are static, impacting the propagation of the signals in a predictable way and that each person, having a unique physique, consistently interferes with that propagation in the same way. It’s a tool that reports “the interference in this room looks like the same interference observed in these past cases.”
Search and rescue is a very dynamic environment, with no opportunity to establish a local baseline, and with a high likelihood that the physiological signal you are looking for has been altered (such as by broken or severed limbs).
There are some other WiFi sniffing technologies that might be more useful for S&R such as movement detection, but I’m not sure if that will work as well when the broadcaster is outside the environment (as the more rubble between the emitter and the target the weaker your signal from reflections against the rubble).
Don’t think of this as being able to see through walls like with a futuristic camera, think of this as AI assisted anomaly detection in signal processing (which is exactly what the researchers are doing).
https://spinoff.nasa.gov/FINDER-Finds-Its-Way-into-Rescuers-Toolkits
Microwave based ground penetrating radar is actually different from WiFi. Also the technology referenced in the link is a motion based body locator, not an identity recognition device.
This is different technology doing different things than what the original article was talking about.