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Wi-Fi Wi-Fi Imaging Wi-Fi Issues
Researchers See Through Walls With Wi-Fi 

New technology recently engineered by scientists at UC Santa Barbara using Wi-Fi signals has enabled people to see objects and read letters through walls.

Your initial reaction to this is probably one of two things:

  1. Wow – Amazing! What a breakthrough
  2. Well this seems like a potential privacy issue further down the line

How have Wi-Fi systems been used to see through walls?

Researchers from UC Santa Barbara developed this system where the edges of solid objects on one side of a solid barrier ie. a wall, can be traced from the other side using WI-Fi signals. This includes letters of the alphabet. 

Imaging the letters individually, in one experiment this technology was used to work out the word ‘believe’ from the other side of a wall, deciphering the letters one by one. 

They did this using 3 standard Wi-Fi transmitters. Over a particular area, these Wi-Fi transmitters sent wireless waves. The imaging was based on measuring the signal power received by a Wi-Fi receiver grid via receivers mounted on a movable vehicle. 

3 transmitters you say – Would that not be triangulation? One of the researchers on this project states that triangulation is not being used. Instead, each transmitter is merely providing a different viewpoint, illuminating the area from different angles. This approach helps to reduce the chance that one of the edges they are detecting will not fall into a ‘blind region.’ To leave a signature on the receiver grid, they need to be ‘seen’. 

The key to the success of this tech system using Wi-Fi signals to see through walls is their edge-based approach. Triangulation in this instance would not perform well. 

How can objects be tracked using Wi-Fi signals?

This tech system is based on the principle of Keller’s Geometric Theory of Diffraction (aka The Keller Cone). 

Keller introduced his Geometrical Theory of Diffraction (GTD) in the 1950s. The development of this theory was revolutionary, as it explained the phenomena of wave diffraction entirely in terms of rays for the first time, via a systematic generalisation of Fermat’s principle. In simple terms, it explains the process of a wave bending around an object (or obstacle) and how it spreads out across a particular space. 

Using the principle of this theory, the system can interpret what could be on the other side of a wall. 

Why is seeing through walls with Wi-Fi something new?

Scientists have actually been attempting to do this for a while, years in fact. This particular team at UC Santa Barbara have been working on this since 2009. This latest engineering breakthrough is significant because it was previously thought that anything as complex as reading the English alphabet through walls using Wi-Fi signals would be too difficult due to the complexity of the lettering. 

Indeed, using Wi-Fi for imaging something still (like letters) has been a challenge due to the lack of motion. However, they seem to have overcome this issue by tracing the edges of the objects.

Back in July, we saw a similar tech engineered by researchers at Carnegie Mellon University where they tracked a 3D shape as well as human bodies moving in a room using Wi-Fi signals. 

Seeing Through Walls With Wi-Fi – What will it be used for?

Assuming that this tech system matures and is put to wider use, we might find it useful for a few different applications: 

  • Crowd analytics
  • Identifying individuals
  • Boosting smart spaces 

Is the resolution high enough? 

Resolution on imagery can be improved by increasing the signals to higher frequencies. However, this would also increase the propagation loss so there would be a trade-off on energy.

This is likely where future experimentation will lie, as researchers and scientists look to explore this energy trade-off as frequencies and propagation loss increase.  

Is it just edges of objects that can be detected? If this tech system of looking through walls with Wi-Fi signals is going to be widely adopted then depth sensing would also be useful. This can be achieved by using a wideband signal for transmission. 

The experiment spoken about in this article was designed to showcase the performance of everyday radio signals, using 802.11n Wi-Fi which is narrowband. However, the framework could easily be expanded to utilise wideband signals too. 

What challenges could ‘seeing through walls’ with Wi-Fi face?

As we stated at the start of this article, some potential issues that could arise from using Wi-Fi signals to see through walls relate to privacy and security. 

Thus, this could have an effect on how successful this new tech system could be. 

Could cyber criminals use this technology in part of an attack? Could law enforcement officials abuse this technology in some contexts?

We wrote on this topic of Wi-Fi seeing through walls back in January, about a similar piece of research that used ‘dense pose’ from Wi-Fi, using Wi-Fi signals as a human sensor and a way to map the position of human bodies using AI. You can read it here.

What are your thoughts on this – We’d love to know! Which camp do you sit in – Amazing Breakthrough or Privacy Nightmare? Get in touch on Facebook, X or Instagram. 

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LiDAR Monitoring Radar Wi-Fi
Can Scientists Use Wi-Fi to Watch Us Through Walls? 

American researchers based in Pennsylvania have shown a way to map the position of human bodies using AI (Artificial Intelligence) and Machine Learning with a deep neural network alongside Wi-Fi signals.

By analysing the phase and amplitude of Wi-Fi signals, Carnegie Mellon University researchers can see where people are, even through walls!

Over the last few years, researchers and scientists have done much work in this area. They’ve been looking at ‘human pose estimation’ which is identifying the joints in the human body and using sensors to work out body position and movement. To experiment with doing this, they’ve looked at:

  • RGB cameras (used to deliver coloured images of people and objects by capturing light in red, green, and blue wavelengths)
  • LiDAR (a Light Detection and Ranging system which works on the principle of radar, but uses light from a laser)
  • Radar (a radiolocation system that uses radio waves to determine the distance, angle, and radial velocity of objects relative to a site)

Why is this useful? Using a type of sensor to detect body position and movement could be used for video gaming, healthcare, AR (Augmented Reality), sports and more. 

The problem is that to do this with imagery (i.e. cameras) can be tricky due to being affected negatively by things like lighting or things obscuring the view. 

And to use radar or LiDAR is not only expensive but requires a lot of power. 

Enter, Wi-Fi. 

Using Wi-Fi Signals as a Human Sensor

The team at CMU in Pennsylvania decided to look into using standard Wi-Fi antennas alongside predictive deep learning architecture in order to detect body position. 

How does it work? Using a deep neural network, the phase and amplitude of Wi-Fi signals are mapped out to UV coordinates within 24 regions of the human body.

Their study revealed that using their model with Wi-Fi signals as the only input, they can estimate the dense pose of multiple subjects. The performance of this method was comparable to other image-based approaches. 

As we said above, other methods use a lot of power and are also expensive. This Wi-Fi method that the ‘DensePose from Wi-Fi’ paper outlines, offers a lower cost alternative that is more widely accessible. It also says that it allows for privacy-preserving algorithms, which means that for human sensing it is less invasive than using Radar or LiDAR tech in non-public areas. 

Although, not much of all this research sounds particularly preserving of privacy does it! 

Has Wi-Fi Been Used as a Human Sensor Before?

Whilst the premise of monitoring people in a room using Wi-Fi isn’t a new one, the actual data previously collected wasn’t very clear, with trouble actually visualising what a person was doing within that room. 

The difference with this new research from CMU is that it is using DeepPose and machine learning technology to not only estimate what the target person is doing, but also clearly make it visual. 

As we said earlier, it’s also more accessible. The model they used needed just 2 wireless routers, each with 3 antennas and worked via the usual 2.4GHz band. 

All you would need to do is put each router and antennas at either side of the target, and then gather the data by having full control of both units. 

Whilst it’s more straightforward than Radar or LiDAR, there are still a couple of flaws. The range is limited by the weakness of Wi-Fi signals, and the accuracy could still be an issue too. 

‘DensePose From Wi-Fi’ Paper Summary

The main things to take from this recent research are:

  • Wi-Fi signals make it possible to identify dense human body poses by using deep learning architectures
  • The public training data in the field of Wi-Fi based perception limits the performance of this current model, especially with different layouts
  • The system has some difficulty identifying and representing body poses that are less common, and also struggles if there are 3 or more people concurrently
  • Future research will aim to look at collecting multi-layout data as well as utilising a bigger data set in order to predicting 3D body shapes using Wi-Fi signals and correctly interpret data

The researchers believe that this Wi-Fi signal model could result in cheap human sensor monitoring as an alternative to RGB cameras and LiDARs.

If you want to read more, you can access the ‘DensePose From Wi-Fi’ paper here.

Here at Geekabit we’re interested to see what comes up when this is peer reviewed. What are your thoughts on using Wi-Fi signals to map and visualise people inside rooms? 

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