Contactless sensing refers to the use of wireless signals, particularly WiFi, to detect, monitor, and interpret human presence, movement, and activity without requiring physical contact with or attachment of any device to the subject. It matters because it enables unobtrusive, privacy-preserving monitoring in environments such as healthcare, smart homes, and security, where wearable or camera-based systems are impractical or invasive. Key variants include near-field and far-field sensing approaches, single-person and multi-person scenarios, and passive sensing techniques that leverage Channel State Information (CSI) or Received Signal Strength Indicator (RSSI) to capture fine-grained physical changes caused by human presence.
Source Papers
- Efficient machine learning for Wi-Fi CSI-based human activity recognition using fast Monte Carlo based feature extraction ↗ — Efficient machine learning for Wi-Fi CSI-based human activit
- OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors ↗ — OPERAnet, a multimodal activity recognition dataset acquired
- Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point ↗ — Passive WiFi Radar for Human Sensing Using a Stand-Alone Acc
- Towards Environment Independent Device Free Human Activity Recognition ↗ — Towards Environment Independent Device Free Human Activity R
- Understanding and Modeling of WiFi Signal Based Human Activity Recognition ↗ — Understanding and Modeling of WiFi Signal Based Human Activi