Semantic Matching Framework for handicap situation detection in smart environments

Article type: Research Article

Authors: Kadouche, Rachid^; | Abdulrazak, Bessam | Mokhtari, Mounir | Giroux, Sylvain | Pigot, Hélène

Affiliations: DOMUS Lab Université de Sherbrooke, Sherbrooke, Québec, Canada | Handicom Lab, Institut National des Télécommunications-GET, Evry, France

Note: [] Corresponding author. E-mail: rachid.kadouche@usherbrooke.ca.

Abstract: In this paper we present a novel approach to detect the handicap situation on a complex living environment for users with special needs. It is built upon formalisms based on Description Logic (DL) named Semantic Matching Framework (SMF). SMF provides an appropriate middleware for supporting assistive services in dynamic environments. This framework is based on the matching of two models: an environment model, describing the environment related services (actuators, devices, etc.) and a user model, containing the description of the user's characteristics (behaviors, preferences, etc.). This Framework was implemented and integrated into a demonstrator (a smart home for dependent people), which is used to validate the smart home concept under laboratory conditions dedicated to dependant people. Performance results are presented to highlight the time response of SMF.

Keywords: Disability, handicap situation, pervasive computing, ubiquitous, smart spaces

DOI: 10.3233/AIS-2009-0031

Journal: Journal of Ambient Intelligence and Smart Environments, vol. 1, no. 3, pp. 223-234, 2009