Movement tracking refers to the continuous monitoring and localization of one or more individuals as they move through a physical environment, using wireless signal perturbations — particularly changes in CSI or RSSI — to infer spatial trajectories, velocity, and directional patterns without requiring subjects to carry any device. It matters to the field because it underpins a broad range of real-world applications including indoor navigation, elderly care monitoring, intruder detection, and smart home automation, demonstrating the practical viability of device-free sensing as an alternative to camera-based or wearable-based systems. Key variants include single-person versus multi-person tracking, coarse-grained zone-level localization versus fine-grained continuous trajectory estimation, and passive versus active sensing configurations, with deep learning approaches increasingly enabling higher spatial resolution and robustness to environmental dynamics.
Source Papers
- A Survey on Wireless Device-free Human Sensing: Application Scenarios, Current Solutions, and Open Issues ↗ — A Survey on Wireless Device-free Human Sensing: Application
- Understanding and Modeling of WiFi Signal Based Human Activity Recognition ↗ — Understanding and Modeling of WiFi Signal Based Human Activi
- WiFi-Based Human Sensing With Deep Learning: Recent Advances, Challenges, and Opportunities ↗ — WiFi-Based Human Sensing With Deep Learning: Recent Advances