A NEURO-FUZZY EMBEDDED SYSTEM FOR INTELLIGENT ENVIRONMENTS

Javier Echanobe, Ines del Campo, Guillermo Bosque

2009

Abstract

Intelligent Environments are endowed with a large number of non-intrusive, embeded electronic systems, such as sensors, microprocessors, actuators, etc. These electronic systems must exhibit intelligent abilities in order to learn and adapt from the users’ habits and preferences. In this paper, we propose a Neuro-Fuzzy electronic embedded system to control several ambient parameters of an intelligent environment, such as temperature, illumination, volume of the sound, and aroma. In particular the PWM-ANFIS model has been selected which provides learning/adaptation features and also fuzzy reasoning. The system is implemented on a reconfigurable device (i.e., FPGA) leading to a small, compact and very efficient electronic system.

References

  1. del Campo, I., Echanobe, J., Bosque, G., and Tarela, J. (2008). Neuro-fuzzy modeling and control. IEEE Transactions on Fuzzy Systems, 16(3):761-778.
  2. Echanobe, J., del Campo, I., Bosque, G., and Tarela., J. (2008). An adaptive neuro-fuzzy system for efficient implementations. Information Sciences, 178:2150- 2162.
  3. ESTO (2003). Science and Technology Roadmapping: Ambient Intelligence in Everyday Life (AmI@Life). European Science and Technology Observatory (ESTO).
  4. ISTAG (2001). Scenarios for Ambient Intelligence in 2010. IST Advisory Group (ISTAG), European Commission Community Research.
  5. ISTAG (2005). Ambient Intelligence: from vision to reality. IST Advisory Group (ISTAG), European Commission Community Research.
  6. Jang, J. . R. (1993). Anfis: Adaptive-network-based fuzzy inference system. IEEE Trans. Systems, Man, and Cybernetics, 23(3):665-685.
  7. Jang, J. . R. and Sun, C.-T., M. (1995). Neuro-fuzzy modeling and control. Proceedings of the IEEE, 83(3):378- 406.
  8. Omondi, A. R. and Rajapakse, J. C. (2006). FPGA Implementations of Neural Networks. Springer.
  9. Schoitsch, E. and Skavhaugh, A. (2006). Embedded intelligence. ERCIM News, 67:14-15.
Download


Paper Citation


in Harvard Style

Echanobe J., del Campo I. and Bosque G. (2009). A NEURO-FUZZY EMBEDDED SYSTEM FOR INTELLIGENT ENVIRONMENTS . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 559-564. DOI: 10.5220/0002321105590564


in Bibtex Style

@conference{icnc09,
author={Javier Echanobe and Ines del Campo and Guillermo Bosque},
title={A NEURO-FUZZY EMBEDDED SYSTEM FOR INTELLIGENT ENVIRONMENTS},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)},
year={2009},
pages={559-564},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002321105590564},
isbn={978-989-674-014-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)
TI - A NEURO-FUZZY EMBEDDED SYSTEM FOR INTELLIGENT ENVIRONMENTS
SN - 978-989-674-014-6
AU - Echanobe J.
AU - del Campo I.
AU - Bosque G.
PY - 2009
SP - 559
EP - 564
DO - 10.5220/0002321105590564