Mind the gaps: Edge-based monitoring for continuous room-level location tracking

Abstract

Abstract In-home monitoring applications often need strong and reliable contextual information to be of value. Indoor location tracking can play an important role in providing this context. However, most current indoor tracking solutions require extensive, application-specific knowledge and pre-deployment preparation, often including detailed information about floorplans and RF signal strength calibration, which is not practical in many deployments. This paper introduces an edge-based location monitoring technique that uses doorway sensors to detect doorway crossing events with walking directions. The approach is designed to provides room-level tracking. Users movement from a wearable device is used in conjunction with the edge-monitored approach to track multiple people. This method also enables the tracked location and doorway crossing events to be transformed into states and state transitions, respectively. This provides an opportunity to implement stochastic models to the edge-based location tracking to correct tracking errors and improve its accuracy, as demonstrated in simulation. This location tracking method has been implemented and deployed in a health monitoring study on dementia-related agitation.