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

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 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.

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

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

The Nest smoke detector microphone was never really secret. It was part of the monthly self test to determine if the alarm was working. It would send you a notification telling you it was going to sound the alarm and that it would be listening for the sound to confirm it was working.

It was listed in the features for the 2nd gen units. https://support.google.com/googlenest/answer/9229922#zippy=%...

>newer Alexa devices have "presence detection"

Not even the biggest privacy issue of using Alexa devices. I think listening you 24/7 is a bigger potential issue.

Not sure if Alexa has this, but cheap mm-wave wideband multi-GHz sensors(or radars more accurately) now enable more finely grained human presence detection and also human fall detection[1] with the right algos, so you can for example detect if grandma in the nursing home fell down and didn't get back up, but in a privacy focused way that doesn't resort to microphones or cameras. Neat.

>Reminds me of the story about how the Google Nest smoke detector had a microphone in it.

Vapes have microphone arrays in them to detect when you're sucking and light up the heating element. Cheap electronics have enabled a new world of crazy.

[1] https://www.seeedstudio.com/MR60FDA2-60GHz-mmWave-Sensor-Fal...

Every capacitor can be a potential microphone ...

First this is not just Android. Apple does the same thing. You can buy an iPad which physically does not have any GPS hardware and it can reasonably tell you where you are. Personally I first learned of this feature when I bought a second-generation iPad, so it’s been there a while ago.

Second, it is a logical leap to assume Google knows everything already. They could for example build this nearby Wi-Fi based location querying API with privacy in mind, by purposefully making it anonymous without associating it with your account, going through relays (such as Oblivious HTTP), use various private set intersection techniques instead. It is tired and lazy to argue that just because some Big Tech has the capability of doing something bad therefore they must already be doing it.

The approach described in the article is much different and more interesting, as it's passive and doesn't require any electronics on the individual being identified.

This is a defeatist attitude.

Run grapheneos!

What happens is that a large body of water (pun intended) has the ability to absorb and reflect wifi signals as it moves through the room. For this you need to generate traffic and measure for instance RSSI or CSI (basically, signal strength) of the packets. If you increase frequency you can detect smaller movements such as arms moving vs. a body, or exclude pets if you reduce sensitivity. It works well for detecting presence and movement in a defined space, but ideally requires you to cross the path between two mains-powered devices, such as light bulbs or wifi mesh points. Passing a cafe doesn't seem too likely.

If you want to do advanced sensing, trying to identify a person, I would postulate you need to saturate a space with high frequency wifi traffic, ideally placed mesh points, and let the algo train on identifying people first by a certain signature (combination of size/weight, movement/gait, breath / chest movements).

Source: I worked on such technologies while at Signify (variants of this power Philips/Wiz "SpaceSense" feature).

More here: https://www.theverge.com/2022/9/16/23355255/signify-wiz-spac...

> So what's the resolution of these images, and what's visible/invisible to them?

The researchers never claimed to generate "images," that's editorializing by this publication. The pipeline just generates a confidence value for correlating one capture from the same sensor setup with another.

[Sidenote: did ACM really go "Open Access" but gate PDF download behind the paid tier? Or is the download link just very well hidden in their crappy PDF viewer?]

Resolution and positional accuracy are very poor. It’s more like ‘an approximate bag of water detector’.

Gait analysis is complete fiction. Especially with a non-visual approach like this.

From the paper linked by jbotz

> The results for CSI can also be found in Figure 3. We find that we can identify individuals based on their normal walking style using CSI with high accuracy, here 82.4% ± 0.62.

If you're a person of interest you could be monitored, your walking pattern internalized in the model then followed through buildings. That's my intuition at practical applications, and the level of detail.

It's at least possible to record heart rate with wifi, so that suggests a broad variety of biometrics can be recorded.

https://arxiv.org/abs/2510.24744

I don't feel that this article is a fair summary of the paper. And the title is just clickbait.

The paper says, in a somewhat contrived scenario, with dozens of labelled walkthroughs per person, they can identify that person from their gait based on CSI and other WiFi information.

This is a long way from identifying one person in thousands or tens of thousands, being able to transfer identifying patterns among stations (the inference model is not usable with any other setup), etc.

All the talk of "images" and "perspectives" is journalistic fluffery. 2.4Ghz and 5Ghz wavelengths (12cm & 6cm) are too long to make anything a layperson call an "image" of a person.

What creepy thing could you actually do with this? Well, your neighbor could probably record this information and tell how many and which people are in your home, assuming that there is enough walking to do a gait analysis. They might be able to say with some certainty if someone new comes home.

That same neighbor could hide a camera and photograph your door, or sniff your WiFi and see what devices are active or run an IMSI catcher and surveil the entire neighborhood or join a corporate surveillance outfit like Ring. Using the CSI on your WiFi and a trained ML model is mostly cryptonerd imaginiation.

Wait a minute while I don my tin-foil pants.

What about rotating MAC address?

Probably. If you look at the paper they wouldn't let their participants wear loose or baggy clothing.

No! That would make you stand out with the fiery intensity of a sun.

Can you say what products make use of this technique? i.e. is it well known like Juniper Mist or not publicly available?

Source?

Microwave frequencies like 2.4 or 5 GHz just passively allow you to do this. You'd have to adopt frequencies that are useless for radar.

I mean you could even jam a microwave oven door open, turn it on, and then measure how much energy loss there was through certain paths. That's essentially all beamforming in Wifi requires -- a really sophisticated way of measuring paths that cause energy loss, and a really sophisticated antenna design that allows you to direct the signal through paths that don't cause energy loss. The first problem is what's facilitating surveillance because humans cause signal loss because our bodies are mostly water, and 2.4 GHz radio waves happen to get absorbed really well by water. This causes measurable signal loss on those paths and the beamforming antennae use that information to route around your body. But they could also just log that information and know where you are relative to the WAP.

That's more than related