Gait recognition based on ground pressure

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Reflective Wi - Fi Recognition . Even if you’re alone in a room, the door is closed, and the curtains are drawn, you can be identified by the way your body reflects Wi-Fi signals. Researchers at MIT have developed a scanner that combines a Wi-Fi emitter, sensors, and AI algorithms. It models the actions of a person on the other side of an opaque barrier. Like sonar, the technology, called RF-Pose, identifies 2D shapes of people and other objects based on the patterns of Wi-Fi signals they reflect. When correlated and cross-trained with AI applications that recognize gait, gestures, and motion, these shapes can identify people 83% of the time.

The University of Manchester has created an AI-based gait malta whatsapp data system called SfootBD with almost 100% accuracy. It uses a passive sensor to analyze weight distribution, speed, and walking style. Ground pressure signals are correlated with the walking style captured by a high-resolution camera. To train the AI, the researchers created a database of gait signals from more than 120 people, measuring floor pressure. The data was collected in public places (airport checkpoints, workplaces) and at home. The algorithm was tested on a control group of gait imitators, as a result of which it was able to recognize attempts to copy someone else's gait.

Activity recognition based on temperature. This technology is nothing new. It is used in construction automation, energy management, security and access control systems. Sensors record the infrared heat emitted by a person or another object. This is one of many parameters detected by a new generation of supersensors that also detect sounds, vibrations, light and electromagnetic radiation. Google is one of many companies that have invested heavily in the AI ​​needed to process all this data in its entirety to accurately recognize human actions and other activity indoors and outdoors.