Exploiting Ambient Wi-Fi Terminals for Human Presence Detection

Abstract

Indoor presence detection is essential for security monitoring in smart spaces, supporting applications such as access control and anomaly detection. While Wi-Fi Channel State Information (CSI) sensing has emerged as a promising solution, most existing methods rely on fixed and stable links, an assumption rarely satisfied in real-world deployments. Indoor environments are naturally populated with opportunistic devices such as smartphones, laptops, and Internet of Things (IoT) terminals, which generate intermittent and heterogeneous CSI streams that are sensitive to environmental interference. These factors reduce sensing stability and make stationary occupants difficult to detect. To address these challenges, we present a practical CSI sensing system tailored to ambient Wi-Fi links with opportunistic connectivity. A reference-based subspace denoising method exploits unoccupied periods to model long-term background statistics and suppress persistent hardware and environmental interference. A multi-region joint sensing strategy further integrates room device-to-Access Point (AP) links with corridor AP-to-AP links, using spatial consistency to capture room states and transitions across regions. This design improves the reliability of presence decisions in security monitoring scenarios, where false alarms may trigger unnecessary responses and missed detections may hide unauthorized or stationary occupants. Evaluation in single-room and four-room university deployments shows that reference-based denoising improves room sensing and that multi-region joint sensing further improves presence inference by incorporating corridor transition cues. Ablations, baseline comparisons, and sensing-risk tests also examine the system behavior under practical deployment conditions. These results indicate that opportunistic Wi-Fi sensing can support presence detection for indoor security monitoring in practical deployments.