- WHOFI uses WI -FI signal distortion to fingerprints Individuals without visual data
- Deep Neural Network Maps signal changes to identify people with near perfect accuracy
- Academic research opens new confidentiality debates around biometric tracking via WI -FI signals
Researchers at La Sapienza University in Rome have created WHOFI, a system that claims to be able to identify individuals by analyzing Wi -Fi signals.
The system traces people by interpreting how their presence interferes with WI -FI patterns and offers a potential alternative to conventional biometric methods.
The technology works by examining channel mode information or CSI, which measures changes in WI -FI signals caused by humans and objects -and a deeply neural network then interprets these disturbances as individual fingerprints.
The researchers claim that the system provides 95.5% accuracy to identify people, even in different environmental conditions.
The team behind Whofi includes Danilo Avola, Daniele Pannone, Dario Montagnini and Emad Emam, who previously suggested a system called Eyefi by 2020. The new system is more accurate and able to re -identify people through non -visual biometric signatures embedded in CSI.
Whofi is not dependent on cameras or physical contact. It only needs an existing WI -FI network to feel human presence and movement.
The technology can work in darkness, through walls and even around obstacles, making it a discreet option compared to video surveillance systems.
The researchers emphasize that Whofi does not collect personal data or reveal identities in the conventional sense, and notice, “By utilizing non -visual biometric features embedded in Wi -Fi CSI, this study offers a privacy preservation and robust approach to Wi -Fi -based re -id, and it is lays the foundation for future work in wireless biometric Sensing. “
It is still clear that the ability to trace individuals without their knowledge is a potential privacy nightmare.
Routine privacy violations can reveal patterns of daily behavior, such as regular locations or movements, which potentially reveal sensitive personal habits.
So far, WHOFI remains an academic project without known plans for commercial or government development. Still, the benefits of monitoring ability are clear. It can bypass poor lighting and crowded environments and is less conspicuous than cameras or visual scanners.
A number of similar Wi-Fi-based detection technologies have emerged in different forms over the years.
Gamgee developed a fall detection system that could warn others if someone fell or if a penetrating came into the home.
Comcast’s XFinity Service introduced Wi-Fi movement that turns everyday units such as smart refrigerators, printers or TVs for motion sensors.
Other researchers have gone on by using Wi-Fi signals to “see” through walls. A UC Santa Barbara team created a system that outlines items and even reads letters through barriers.
A similar study by Carnegie Mellon University demonstrated how standard Wi-Fi routers can detect a person’s location and body position in a room.
You can read more about the research behind Whofi in this paper published on Arxiv Preprint server.
Via Tech Xplore
