WiFi sensing is a passive or active monitoring technique that leverages the physical layer properties of WiFi signals — most commonly Channel State Information (CSI) — to detect, classify, or quantify physical phenomena such as human presence, movement, and occupancy without requiring dedicated sensors or wearable devices. It matters because it enables scalable, cost-effective, and privacy-preserving environmental monitoring by repurposing existing wireless infrastructure, with applications spanning smart buildings, public transport, and crowd management. Key variants include device-based and device-free approaches, single versus multiple transceiver configurations, and the use of different classification or regression backends ranging from traditional machine learning to deep learning architectures such as CNN+LSTM models.

Source Papers

  • A Framework to Estimate Classroom Occupancy using WiFi Channel State Information — A Framework to Estimate Classroom Occupancy using WiFi Chann
  • CSI-Based People Counting in WiFi Networks: Leveraging Occupancy Detection — CSI-Based People Counting in WiFi Networks: Leveraging Occup
  • CSI-based Passenger Counting on Public Transport Vehicles with Multiple Transceivers — CSI-based Passenger Counting on Public Transport Vehicles wi
  • CrossSense: Towards Cross-Site and Large-Scale WiFi Sensing — CrossSense: Towards Cross-Site and Large-Scale WiFi Sensing
  • DASECount: Domain-Agnostic Sample-Efficient Wireless Indoor Crowd Counting via Few-Shot Learning — DASECount: Domain-Agnostic Sample-Efficient Wireless Indoor
  • Deep Learning-Enhanced Human Sensing with Channel State Information: A Survey — Deep Learning-Enhanced Human Sensing with Channel State Info
  • Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT — Device-free occupancy detection and crowd counting in smart
  • 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
  • Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond — Integrated Sensing and Communications: Toward Dual-Functiona
  • Investigation of Environment Dependence in Wi-Fi CSI-Based Crowd Counting Systems — Investigation of Environment Dependence in Wi-Fi CSI-Based C
  • Occupancy Prediction in IoT-Enabled Smart Buildings: Technologies, Methods, and Future Directions — Occupancy Prediction in IoT-Enabled Smart Buildings: Technol
  • Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point — Passive WiFi Radar for Human Sensing Using a Stand-Alone Acc
  • Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review — Sensing Technologies for Crowd Management, Adaptation, and I
  • Tool release — Tool release
  • Towards Environment Independent Device Free Human Activity Recognition — Towards Environment Independent Device Free Human Activity R
  • WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and Opportunities — WiFi-Based Human Sensing With Deep Learning: Recent Advances
  • WiGNN: WiFi-Based Cross-Domain Gesture Recognition Inspired by Dynamic Topology Structure — WiGNN: WiFi-Based Cross-Domain Gesture Recognition Inspired