Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Smart home care network using sensor fusion and distributed vision-based reasoning
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
The Method of Location Error Detection and Correcting in Smart Home Environments
ICHIT '06 Proceedings of the 2006 International Conference on Hybrid Information Technology - Volume 02
Bayesian Filtering and Anonymous Sensors for Localization in a Smart Home
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02
Bayesian Filtering for Location Estimation
IEEE Pervasive Computing
Incorporating duration information in activity recognition
KSEM'10 Proceedings of the 4th international conference on Knowledge science, engineering and management
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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 is addressing 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 functional in real conditions. We conceived an experiment to estimate precisely its accuracy and evaluate its robustness. The experiment consists of a scenario of daily routine meant to maximize the occupant's motion in meaningful activities. It was performed by 14 subjects, one subject at a time. The results are satisfactory: the system's accuracy exceeds 85% and is independent of the occupant's profile. The system works in real time and behaves well in presence of noise.