Model-Based Location Tracking of an a priori Unknown Number of Inhabitants in Smart Homes

In this paper, we propose an approach for online model-based location tracking of inhabitants in Smart Homes. Based on our previous solution for a fixed and predefined number of inhabitants using finite automata, we generalize the approach to handle an a priori unknown number of inhabitants. The online algorithms to detect the number of inhabitants and to track their location are given, and a comprehensive evaluation method is defined. It consists of an analytical and a simulation-based procedure as well and is able to predict the tracking performance for real Smart Homes by a normalized measure. Throughout the paper, previous and new results are illustrated by a realistic case study and illustrative scenarios are given. Tracking the location of several inhabitants in a Smart Home using only ambient, noninvasive, low-cost sensors is a challenge. In this paper, we propose specific evaluation approaches as well as an expert-in-the-loop improvement procedure to help the expert setting up a satisfying instrumentation using only such sensors. We also detail the algorithm for online Location Tracking of any inhabitants in a Smart Home and explain this algorithm with an illustrative scenario.