Optimizing Building's Environments Performance Using Intelligent Systems

  • Authors:

  • E. Sierra;A. Hossian;D. Rodríguez;M. García-Martínez;P. Britos;R. García-Martínez

  • Affiliations:

  • Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...;Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...;Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...;Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...;Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...;Software & Knowledge Engineering Center. Buenos Aires Institute of Technology, Confluencia Academic Unit, National University of Technology- University of Comahue, School of Architecture. Universi ...

  • Venue:
  • IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
  • Year:
  • 2008

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Abstract

This article describes an intelligent system architecture that based on neural networks, expert systems and negotiating agents technologies is designed to optimize intelligent building's performance. By understanding a building as a dynamic entity capable of adapting itself not only to changing environmental conditions but also to occupant's living habits, high standards of comfort and user satisfaction can be achieved. Results are promising and encourage further research in the field of artificial intelligence applications in building automation systems.