Passive Sensing

Passive sensing focuses on extracting information from the environment without actively emitting signals, aiming to achieve non-intrusive monitoring and data acquisition. Current research emphasizes developing robust algorithms, including autoencoders, Hidden Markov Models, and transformer networks, for processing data from diverse sources like audio, video, and Wi-Fi signals to detect and classify events or behaviors. This field is significant for applications ranging from structural health monitoring and activity recognition in healthcare to environmental surveillance and robotics, offering cost-effective and scalable solutions for various monitoring tasks.