Semantic Matching Framework for handicap situation detection in smart environments

  • Authors:
  • Rachid Kadouche;Bessam Abdulrazak;Mounir Mokhtari;Sylvain Giroux;Hélène Pigot

  • Affiliations:
  • (Correspd. E-mail: rachid.kadouche@usherbrooke.ca) DOMUS Lab Université de Sherbrooke, Sherbrooke, Québec, Canada;DOMUS Lab Université de Sherbrooke, Sherbrooke, Québec, Canada;Handicom Lab, Institut National des Télécommunications-GET, Evry, France;DOMUS Lab Université de Sherbrooke, Sherbrooke, Québec, Canada;DOMUS Lab Université de Sherbrooke, Sherbrooke, Québec, Canada

  • Venue:
  • Journal of Ambient Intelligence and Smart Environments
  • Year:
  • 2009

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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.