Scientists show routers can be used to track your movements through walls

Researchers at Carnegie Mellon University have developed a unique Wi-Fi setup that allows them to estimate human movements through walls and dense objects. What’s interesting is that they don’t need expensive equipment, like specialized LiDAR devices or cameras, to make this work. They were able to achieve this with low-cost $30 Wi-Fi routers and receivers, which raises some privacy concerns.

Leveraging a tool called DensePose from Facebook’s AI Lab, the system analyzes invisible Wi-Fi radio signals that permeate a space and creates a visual model. Radio signals broadcast by a Wi-Fi router naturally bounce off objects and people, and the reflected signals carry information that can be filtered by AI to reconstruct body posture and movements. In the same way that LiDAR or echolocation can be used to create a rough three-dimensional representation of rooms or an area, DensePose can produce images of humans and, over time, could be extrapolated to track and understand a person’s movements.

This has already been done. Years ago, MIT researchers built a similar system, using RF-Capture technology, but the models presented were not as high quality as those obtained with the CMU team and the DensePose recreations. The key to DensePose is what the researchers describe as a “deep neural network that maps the phase and amplitude of Wi-Fi signals to UV coordinates in 24 human regions.” With Wi-Fi signals as the only input, this AI model can estimate the pose of multiple subjects.

Although the CMU study has not yet been peer-reviewed, the scientists demonstrate that their DensePose-driven system can be used to monitor human movement inside a building. But there are a few things to keep in mind. To begin, they use a developed neural network model to make the estimations and exploit the data. This includes training the model on the layout of rooms and spaces. Although DensePose Github is accessible to everyone, the trained model is not. Bad actors should access or develop their own for active surveillance, and train extensively using known spatial configurations.

Additionally, the study does not address the effectiveness of the technology in your average residential home. The researchers used relatively inexpensive devices, but they needed multiple access points: the radio waves came from three routers and three receivers. Without a mesh router system, people might only have one router and one or two repeaters placed throughout their home. It’s unclear what impact this would have on the models. Additionally, in the average home, there are many things that can interfere with Wi-Fi signal strength, which could also be a factor for a system so dependent on reliable readings.

However, larger facilities with multiple network devices (such as hospitals, offices, or commercial buildings) and access to higher quality signals may be able to provide sufficient information. The study also points out that challenges increase when trying to track multiple subjects, so it may be more difficult to track an entire family or groups of people using something like this.

Regardless, research demonstrates that it is possible to locate and track subjects using only Wi-Fi as input. In the study, CMU researchers imagine the technology could be used to monitor the “well-being” of a home’s residents or “identify suspicious behavior.” Questions then arise: who is monitoring, what would be considered “suspicious” and what actions should be taken when strange behavior is detected?

Going further, if the technology were commercialized in some way and used for market research or data collection purposes, it wouldn’t take much to understand the extent of the privacy issues. Reports show that 80% of American households have a home network router, which means open access to Wi-Fi signals in their home. Wi-Fi imaging could enable passive surveillance both in homes and other buildings, without physical access and without consent. Additionally, a general difference between Wi-Fi and wireless Internet is that Wi-Fi is used to distribute the network in a limited space. This is how Wi-Fi networks remain active when the Internet is down, and in this case such a system could be re-engineered to work locally without Internet access.

For now, the limitations may hold him back until someone finds alternative solutions. However, it is unclear how long this would take. Future networking technologies, which are already here and solve the biggest problems of previous Wi-Fi generations, could make consumer routers more powerful and viable for something like this.