Device-free wireless sensing refers to the use of ambient radio frequency signals, such as WiFi, to detect, localize, or monitor people and activities without requiring the tracked individuals to carry or interact with any dedicated device. This approach matters because it enables passive, unobtrusive sensing in environments like classrooms or smart homes using infrastructure that is already widely deployed, making it practical and scalable without imposing a burden on end users. Key variants include occupancy estimation, activity recognition, fall detection, and localization, with underlying models such as the Fresnel zone model, which relates physical movement to signal disruption along propagation paths, and the CSI-ratio model, which suppresses noise by computing ratios between subcarrier measurements to improve sensing robustness.
Source Papers
- A Framework to Estimate Classroom Occupancy using WiFi Channel State Information ↗ — A Framework to Estimate Classroom Occupancy using WiFi Chann
- NeRF2: Neural Radio-Frequency Radiance Fields ↗ — NeRF2: Neural Radio-Frequency Radiance Fields
- WiFi CSI-based device-free sensing: from Fresnel zone model to CSI-ratio model ↗ — WiFi CSI-based device-free sensing: from Fresnel zone model