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Engineering Ambient Intelligence Services by Means of MABS

  • Teresa García-Valverde
  • Alberto García-Sola
  • Francisco Lopez-Marmol
  • Juan A. Botia
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 71)

Abstract

In this work, the methodology AmISim to test and to deployment of Ambient Intelligence (AmI) system is presented. The development of AmI systems is a complex task because this technology must adapt to users and contextual information as well as unpredictable and changeable behaviours. So, we focused in how the methodology AmISim can help to the engineering of adaptative services for users. In this case, we propose a predictor of location based on Hidden Markov Models (HMMs). So, the system can offer Location-Based Services(LBS) that adapt to the users. To this end, we propose a methodology based on a previous social multi-agent based simulation (MABS) and a following deployment of the service in a real environment.

Keywords

Hide Markov Model Real Environment Ubiquitous Computing Hide State Ambient Intelligence 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Teresa García-Valverde
    • 1
  • Alberto García-Sola
    • 1
  • Francisco Lopez-Marmol
    • 1
  • Juan A. Botia
    • 1
  1. 1.University of Murcia 

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