When You Come in, You Sit, Stand, or Walk: Leveraging RSSI for Tracking and Control in Ubiquitous Systems

Ubiquitous systems enable seamless access to information and services with minimal human intervention, operating deliberately through interconnected devices and sensors. Leveraging radio signals from Wi-Fi, this work presents two pilot studies using IEEE 802.11 signal strength for Wireless Signal Strength-based Posture (WiSSP) and Wireless Signal-based Crowd Counter (WiCC). Unlike previous approaches, we use a smartphone application to monitor Received Signal Strength Indicator (RSSI) values from routers in proximity, identifying activities such as entry and exit, sitting, walking, and standing without dedicated router installations. WiSSP tracks postures (sitting and standing) and provides alerts for prolonged sitting, while WiCC estimates office occupancy by counting individuals entering or leaving, all while preserving privacy. Additionally, WiCC can recognize patterns of two people walking or crossing paths together, both inside and outside the office. Our machine learning models, trained on collected signal strength data, achieved approximately 85% accuracy. These studies highlight the potential of Wi-Fi signal strength for enhancing real-time monitoring and control in ubiquitous environments.