• DocumentCode
    2429441
  • Title

    Artificial neural network based e-nose and their analytical applications in various field

  • Author

    Jamal, Maria ; Khan, M.R. ; Imam, S.A. ; Jamal, Arif

  • Author_Institution
    ECE Dept., GGSIPU, Delhi, India
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    691
  • Lastpage
    698
  • Abstract
    A brief and historical overview of research and development in the field of artificial neural network based electronic nose system is presented. Electronic-nose devices have received considerable attention in the field of sensor technology during the past twenty years, largely due to the discovery of numerous applications derived from research in diverse fields of applied sciences. Electronic/artificial noses are being developed as systems for the automated detection and classification of odors, vapors, and gases. An electronic nose is generally composed of a chemical sensing system (e.g., sensor array or spectrometer) and a pattern recognition system (e.g., artificial neural network). We are developing electronic noses for the automated identification of volatile chemicals for environmental, medical applications, commercial industries, including the agricultural, biomedical, cosmetics, food, manufacturing, military, pharmaceutical, regulatory applications and various scientific research fields. This paper is a review of the major electronic nose technologies, developed since this specialized field was born and became prominent in the mid 1980s, and a summarization of some of the more important and useful applications that have been of greatest benefit to man.
  • Keywords
    chemical engineering computing; electronic noses; neural nets; pattern recognition; artificial neural network based e-nose; automated volatile chemicals identification; chemical sensing system; electronic nose system; pattern recognition system; sensor technology; Arrays; Artificial neural networks; Chemicals; Electronic noses; Instruments; Temperature sensors; Artificial Neural Network; Back propagation algorithm; e-nose; multilayer Feed-forward network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Automation Robotics & Vision (ICARCV), 2010 11th International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-7814-9
  • Type

    conf

  • DOI
    10.1109/ICARCV.2010.5707409
  • Filename
    5707409