SAFER: An IoT-based perpetual safe community awareness and alerting network

Abstract

Perpetual awareness systems are sensing systems characterized by continuous monitoring and ubiquitous sensing; they are essential to many safety and mission-critical applications, e.g. assisted living, healthcare and public safety. In this paper, we present SAFER, a perpetual heterogeneous IoT system; deployed in homes to detect critical events (injury, hazardous-environment) that must trigger immediate action and response. A key challenge here is the energy consumption associated with perpetual operations. We propose a novel energy-aware perpetual home IoT system where battery-operated and wall-powered IoT devices co-execute to ensure safety of occupants. We use a semantic approach that extracts activities-of-daily-living from device data to drive energy-optimized sensor activations. To validate our approach, we developed an elderly fall detection system using multi-personal and in-situ sensing devices. Using initial measurements to drive larger simulations, we show that our Cost-Function-Gradient algorithm can achieve greater than 4X reductions in energy dissipation without loss of sensing accuracy.