This is a VERY controlled environment - and they used 20 passes of each person walking with direct knowledge of each person to train for identity. They did no tests with multiple people walking at the same time, or with any other external moving distortion effects (doors opening, etc) . This is very far from actual 'identification' of people in real public settings - and no doubt the cell phone everyone is carrying with them offers many orders of magnitude better opportunity. In a real crowded environment this would be nearly worthless.

The devices that reported BFI information were also stationary, and there were no extra devices transmitting information that would be conflicting.

A single camera would be much more effective.

Yes, but things could be refined. With more resources and research thrown at it, it could become more versatile, that's why the title of the post says "could". And chances are, there are private and government entities already doing this. Research like this has been coming out for at least a decade now.

Even Xfinity has motion detection in homes using this technique now:

https://www.xfinity.com/hub/smart-home/wifi-motion

Yes, you won't be able to do this on normal wifi traffic typically either, you need to send specific packets at a high enough rate (in between normal internet traffic) in order to sense with any accuracy, as I also remarked earlier: https://news.ycombinator.com/item?id=46976849

Yes it's in a controlled environment not in a real world noisy environment. But this is more stealthy than a camera and could potentially work with non-line-of-sight or even through walls.

And based on that I could imagine with a combination of a camera and this method, you could train the model on data where both the camera and this method is seeing the individual and then continue to track them with the wifi sensing + the trained model even where the camera cannot see them anymore.

But yea real world is noisy, so it could be very challenging.

Unless they start storing data about your specific gait & posture, skull shape, limb dimensions and build up a "fingerprint" of your body.

Exactly. All of these stories using WiFi to detect things with high accuracy are just extreme machine learning demos.

Given a tightly controlled environment and enough training data, you can use a lot of things as sensors.

These techniques are not useful for general purpose sensing, though. The WiFi router in your home isn't useful for this.

Yeah I've seen this same type of study done over the years with the same dire warning. But like you pointed out it's just extremely labor intensive when it's simply easier to attack phones, security cameras or any other smart device that can be easily hacked. Or just install your own bugs.

Would not be surprised to see this get more traction right now due to the political climate.

Yeah this is one of those "cool demo" research results that is completely impractical in the real world that is sold (probably by university PR departments) as an actual viable technique that might have real-world implications.

We've seen it before with things like taking photos around corners.

And no, it isn't like the Wright flyer and a bit crap now but in 40 years we have jet planes. This will never get significantly better.

Well nowadays you individually track by using mac addresses and other network information from the devices within range. Cisco has some creepy real time maps of your location with each person walking around and all their previous visits etc

This is going into the next Wifi standard specifically to get this data off of normal wifi traffic.