As Wi-Fi signals travel through a room, they hit walls, furniture and the human body. People’s movements and physical characteristics cause small changes in the way radio waves are propagated.
By analyzing these changes with the help of artificial intelligence, researchers can obtain information about the people in the environment. Researchers at the Karlsruhe Institute of Technology (KIT) in Germany showed that the method can work even if the person does not have a Wi-Fi connected phone with him. Researchers liken the system to a type of imaging method that uses radio waves instead of light.
WI-FI SIGNAL TURNS INTO A BIOMETRIC TRACE
One of the remarkable studies in this field is the “WhoFi” system developed by researchers at Sapienza University of Rome.
The system analyzes data known as “Channel State Information” (CSI) in Wi-Fi networks. Signal changes that occur as a result of the interaction of the human body with Wi-Fi waves are processed by the deep learning system and a type of biometric signature unique to the person can be created.
Thus, it becomes possible to recognize people again via Wi-Fi signals instead of camera images used in classical facial recognition systems.
WALLS MAY NOT BE AN OBSTACLE TOO
One of the most striking aspects of the technology is that radio waves are not affected by some obstacles encountered by visual surveillance systems.
Unlike cameras, in Wi-Fi-based systems, low light, the person turning their back to the camera, or partially obstructing the image may not cause as much of a problem. Wi-Fi sensing technologies have also been previously used to detect human movements and body positions.
NEW RESEARCH IS ALSO COMING
The studies are not limited to identification. New research published in August 2026 also studies the recognition of human activities by artificial intelligence using Wi-Fi signals.
In experiments of a new system called “WiFuse”, activity recognition accuracy of up to 98.20 percent was achieved in some data sets. In another current research, a new data set consisting of more than 22 thousand walking samples was prepared for tracking and identifying people in closed spaces using Wi-Fi and acoustic signals.
PRIVACY CONCERN
Technology; It has significant potential for use in areas such as detecting falls in the elderly, smart home systems, security and contactless health monitoring. However, the same features also raise the possibility of people being monitored without cameras and without them being aware of it.
Although the research is still in the experimental stage, it shows that Wi-Fi networks can turn into a sensor network that can detect people and movements around it in the future, rather than just an infrastructure that carries data.
