Bayesian Filtering and Anonymous Sensors for Localization in a Smart Home

In the context of a constantly increasing aging population with cognitive deficiencies, insuring the autonomy of the elders at home becomes a priority. The DOMUS laboratory aims to address this issue by conceiving a smart home which can both assist people and preserve their quality of life. Obviously, the ability to monitor properly the occupant's activities and thus provide the pertinent assistance depends highly on location information inside the smart home. This paper proposes a solution to localize the occupant thanks to Bayesian filtering and a set of anonymous sensors disseminated throughout the house. The localization system is designed for a single person inside the house. It could however be used in conjunction with other localization systems in case more people are present. Our solution is already functional in real conditions. The preliminary results are encouraging: location estimation exceeds 85% certainty in most cases. We conceived an experiment to estimate precisely the system's accuracy. The experiment consists of a scenario of daily routine that maximizes the occupant's motion in meaningful activities and will be performed by 30 volunteers. We conclude the paper by discussing possible continuations of this work.