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A team of researchers from the University of California at Santa Barbara led by Professor Yasamin Mostofi was for the first time able to identify a person behind a wall using a Wi-Fi signal and video recording.
The developed method, called XModal-ID, involves the use of a Wi-Fi signal transmitter and receiver and a previously recorded video recording of a person's movement. With the help of video recording, a three-dimensional model of a person is formed to simulate changes in the parameters of the Wi-Fi signal reflected from it and draw up a reference graph of such changes.
The standard allows you to identify a specific person behind an obstacle. With the help of the transmitter, the Wi-Fi signal is sent behind the wall and captured by the receiver after being reflected. The graph of the reflected signal is then compared to the reference graph. The XModal-ID method was tested on 8 participants. The accuracy varied depending on the material of the obstacle and averaged 84%.
Researchers believe that the new method will help, for example, the police identify a criminal who has previously been caught on surveillance cameras in a particular room.