An Indoor Localization System for Telehomecare Applications

Abstract. In this paper, we present a novel probabilistic technique, based on the Bayes filter, able to estimate the user location, even with unreliable sensor data coming only from fixed sensors in the monitored environment. Our approach has been extensively tested in a home-like environment, as well as in a real home, and achieves very good results. We present results on two datasets, representative of real life conditions, collected during the testing phase. We detect the patient location with subroom accuracy, an improvement over the state of the art for localization using only environmental sensors. The main drawback is that it is only suitable for applications where a single person is present in the environment, like as with other approaches that do not use any mobile device. For this reason, we introduced the “telehomecare” term, therefore differentiating from generic telemedicine applications, where many people can be in the same environment at the same time.

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Recommended citation: @ARTICLE{7366609, author={A. L. {Ballardini} and L. {Ferretti} and S. {Fontana} and A. {Furlan} and D. G. {Sorrenti}}, journal={IEEE Transactions on Systems, Man, and Cybernetics: Systems}, title={An Indoor Localization System for Telehomecare Applications}, year={2016}, volume={46}, number={10}, pages={1445-1455}, keywords={Bayes methods;filtering theory;indoor navigation;indoor radio;probability;sensor placement;telemedicine;wireless sensor networks;indoor localization system;telehomecare applications;probabilistic technique;Bayes filter;testing phase;environmental sensors;mobile device;telemedicine;Monitoring;Tracking;Senior citizens;Cameras;Uncertainty;Cybernetics;Probabilistic logic;Indoor localization;motion sensor;smart home;telehomecare;wireless sensor network}, doi={10.1109/TSMC.2015.2503339}, ISSN={2168-2232}, month={Oct},}