A context-aware middleware for ambient intelligence

  • Authors:
  • Tao Xu;Bertrand David;René Chalon;Yun Zhou

  • Affiliations:
  • Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS, France;Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS, France;Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS, France;Université de Lyon, CNRS, Ecole Centrale de Lyon, LIRIS, France

  • Venue:
  • Proceedings of the Workshop on Posters and Demos Track
  • Year:
  • 2011

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Abstract

By the acronym MOCOCO we refer to our view of ambient intelligence (AmI), pointing out three main characteristics: Mobility, Contextualization and Collaboration. The ambient intelligence is a challenging research area focusing on ubiquitous computing, profiling practices, context awareness, and human-centric computing and interaction design. We are concretizing our approach in a platform called IMERA (French acronym for Computer Augmented Environment for Mobile Interaction). In order to make work together several sensors, actuators and mobile smart devices, the need of a context-aware middleware for this platform is obvious. In this paper, we present main objectives and solution principles concretized in a context-aware middleware based on hybrid reasoning engine (the ontology reasoning and the decision tree reasoning), which retrieves efficiently high-level contexts from raw data. This platform provides an environment for rapid prototyping of context aware services in Ambient Intelligent (AmI).