Detecting Human Presence via Smartphone BLE Beaconing: Preliminary Investigations

This poster presents preliminary investigations into detecting human presence using Smartphone Bluetooth Low Energy (BLE) beacon signals. By treating smartphones as proxies for individuals, we summarize BLE signal visibility with privacy-aware features such as Stable Neighbors, Presence Counts, Turnover Rates, and Signal Strength statistics. Early findings from other research works suggest these stability-based summaries can effectively track occupancy and movement in indoor and public spaces, offering tiered density estimates rather than exact counts. We discuss several key challenges for this approach, including the presence of multiple devices per person, stationary IoT beacons, other irrelevant devices, and environmental variability. We emphasize the importance of conservative thresholds and space-specific calibration to minimize bias while preserving individual privacy. Potential applications include Crowd Awareness, Smart Buildings, Accessibility, Intelligent Transportation, and Adaptive Interfaces, among others. Future directions could involve calibrating this method, implementing lightweight multimodal fusion, and incorporating ethical safeguards for privacy-respecting implementations.