CFP last date
20 January 2025
Reseach Article

Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach

by Hamid Reza Naji, Morteza Nabi Meybodi, Taha Nejad Falatouri
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 14 - Number 6
Year of Publication: 2011
Authors: Hamid Reza Naji, Morteza Nabi Meybodi, Taha Nejad Falatouri
10.5120/1890-2254

Hamid Reza Naji, Morteza Nabi Meybodi, Taha Nejad Falatouri . Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach. International Journal of Computer Applications. 14, 6 ( February 2011), 9-14. DOI=10.5120/1890-2254

@article{ 10.5120/1890-2254,
author = { Hamid Reza Naji, Morteza Nabi Meybodi, Taha Nejad Falatouri },
title = { Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 14 },
number = { 6 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 9-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume14/number6/1890-2254/ },
doi = { 10.5120/1890-2254 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:02:39.857567+05:30
%A Hamid Reza Naji
%A Morteza Nabi Meybodi
%A Taha Nejad Falatouri
%T Intelligent Building Management Systems by Using Hardware Multi Agents: Fuzzy Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 14
%N 6
%P 9-14
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Growing needs of humanity have forced him to use modern technology in all aspects of his life. Intelligent buildings are one of these modern technologies that have great advantages for people. These buildings include a set of integrated and dynamic systems to manage the allocation of resources and facilitate the residents’ lives. In this context and due to high speed, reliability and better respond to environmental changes, we simulate such environment using hardware multi agents with fuzzy approach. To do this, we use Matlab and its fuzzy toolbox. The results shows that parallel processing nature in this kind of multi agents improve the speedup of the system.

References
  1. Wong, J.K.W., H. Li, and S.W. Wang. 2005, Intelligent building research: a review. Automation in Construction. 14: p. 143– 159.
  2. Ren, Z. and C.J. Anumba. 2004, Multi-agent systems in construction-state of the art and prospects. Automation in Construction. 13(3): p. 421-434.
  3. Rodin, V., et al. 2004, An immune oriented multi-agent system for biological image processing. Pattern Recognition. 37(4): p. 631-645.
  4. Guo, Q. and M. Zhang. 2009, A novel approach for multi-agent-based Intelligent Manufacturing System. Information Sciences. 179(18): p. 3079-3090.
  5. Chen, K.-Y. and C.-J. Chen. 2010, Applying multi-agent technique in multi-section flexible manufacturing system. Expert Systems With Applications. 37(11): p. 7310-7318.
  6. Vengattaraman, T., et al. 2011, An application perspective evaluation of multi-agent system in versatile environments. Expert Systems With Applications. 38(3): p. 1405-1416.
  7. Hagras, H., et al. 2003, A hierarchical fuzzy–genetic multi-agent architecture for intelligent buildings online learning, adaptation and control. Information Sciences. 150: p. 33-57.
  8. Wong, J.K.W. and H. Li. 2008, Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent building systems. Building and Environment. 43: p. 108–125.
  9. Doukas, H., C. Nychtis, and J. Psarras. 2009, Assessing energy-saving measures in buildings through an intelligent decision support model. Building and Environment. 44: p. 290– 298.
  10. Etik, N., et al. 2009, Fuzzy expert system design for operating room air-condition control systems. Expert Systems with Applications. 36: p. 9753–9758.
  11. Singh, J., N. Singh, and J.k. Sharma. 2006, Fuzzy modeling and control of HVAC system - A review. Journal of Scientific & Industrial Research. 65: p. 470-476.
  12. Carrascosa, C., et al. 2008, Hybrid multi-agent architecture as a real-time problem-solving model Expert Systems with Applications. 34(1): p. 2-17.
  13. Neufert, E., et al. 2000, Architects' data: Blackwell Science.
  14. Naji, H.R., et al. 2002. Parallel Image Processing With Agent-based Reconfigurable Hardware. in 15th International Conference on Parallel and Distributed Computing Systems (PDCS 2002). Louisville, KY.
  15. Naji, H.R., B.E. Wells, and L. Etzkorn. 2004, Creating an Adaptive Embedded System by Applying Multi Agent Techniques to Reconfigurable Hardware Future Generation Computer Systems. 20(6): p. 1055-1081.
  16. Kahraman, C. 2008, Multi-criteria decision making methods and fuzzy sets. Springer Optimization and Its Applications. 16: p. 1-18.
Index Terms

Computer Science
Information Sciences

Keywords

Intelligent building hardware multi agents fuzzy model