Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data
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,...
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doaj-ba4ad9e59b9f46e8972483d77dd118a12020-11-24T22:48:04ZengHindawi LimitedInternational Journal of Telemedicine and Applications1687-64151687-64232008-01-01200810.1155/2008/142803142803Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental DataYoucef Rahal0Hélène Pigot1Philippe Mabilleau2Laboratoire DOMUS, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, QC, J1K 2R1, CanadaLaboratoire DOMUS, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, QC, J1K 2R1, CanadaLaboratoire DOMUS, Université de Sherbrooke, 2500 boulevard de l'Université, Sherbrooke, QC, J1K 2R1, CanadaIn 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.http://dx.doi.org/10.1155/2008/142803 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Youcef Rahal Hélène Pigot Philippe Mabilleau |
spellingShingle |
Youcef Rahal Hélène Pigot Philippe Mabilleau Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data International Journal of Telemedicine and Applications |
author_facet |
Youcef Rahal Hélène Pigot Philippe Mabilleau |
author_sort |
Youcef Rahal |
title |
Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data |
title_short |
Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data |
title_full |
Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data |
title_fullStr |
Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data |
title_full_unstemmed |
Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data |
title_sort |
location estimation in a smart home: system implementation and evaluation using experimental data |
publisher |
Hindawi Limited |
series |
International Journal of Telemedicine and Applications |
issn |
1687-6415 1687-6423 |
publishDate |
2008-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2008/142803 |
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