BESI: Reliable and Heterogeneous Sensing and Intervention for In-home Health Applications

Advances in sensing, wireless communication, and data analytics have enabled various monitoring systems for smart health applications. However, many challenges remain to deploy such systems in actual homes, such as achieving robustness, unobtrusiveness, fault tolerance, privacy, and minimal user burden. This paper presents how these challenges were overcome in the realization and successful prototype deployment of the Behavioral and Environmental Sensing and Intervention (BESI) system. BESI is designed to sense behavioral activities using wearables and monitor environmental parameters with in-home sensors. With such data, behavioral patterns can then be modeled to determine associations with environmental attributes and, when appropriate, real-time notifications or interventions can be made based on these models. Challenges in building platforms with residential deployment constraints are discussed. BESI is currently deployed for an in-home study on dementia, and the results are presented to illustrate data collection procedures and system performance.