Tangible ambient intelligence with semantic agents in daily activities

  • Authors:
  • Sébastien Dourlens;Amar Ramdane-Cherif;Eric Monacelli

  • Affiliations:
  • LISV, University of Versailles Saint Quentin, Centre Universitaire de Technologie, 10/12 Avenue de l'Europe --78140 Vélizy, France. E-mail: {sdourlens,rca,eric.monacelli}@lisv.uvsq.fr;LISV, University of Versailles Saint Quentin, Centre Universitaire de Technologie, 10/12 Avenue de l'Europe --78140 Vélizy, France. E-mail: {sdourlens,rca,eric.monacelli}@lisv.uvsq.fr;LISV, University of Versailles Saint Quentin, Centre Universitaire de Technologie, 10/12 Avenue de l'Europe --78140 Vélizy, France. E-mail: {sdourlens,rca,eric.monacelli}@lisv.uvsq.fr

  • Venue:
  • Journal of Ambient Intelligence and Smart Environments
  • Year:
  • 2013

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Abstract

A system should be able to interact with an ubiquitous network of heterogeneous sensors and actuators in order to exploit the maximum available information. Event intensive environment, reactive systems, multiple communication languages and integration of various devices make the architecture and the final system so complex that performance and efficiency tend to be widely affected. Existing solutions are mostly dedicated in solving particular problems. The proposed solution is a different approach to extract the meaning of the situation using semantic agents in order to manage the interaction processes in the human environment. Our components, semantic agents and services, are web services to compose the architecture and act in the environment. Agents possess a new rational memory and an inference engine in order to model and reason with words on entities behaviours. Agents and services exchange events in a knowledge representation language KRL close to natural language. They work together to ensure an ambient intelligence for taking care of disable or elderly people at home. Two important points are highlighted: First, building the architecture with several scenarios of composition of services and agents. Second, how agents and services will interact to provide support.