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On Some Aspects of Odour Detection System

Affiliations

  • Banking and Finance Department, TCS, Kolkata - 700091, West Bengal, India
  • Department of CSE, VITAM, Berhampur - 761008, Odisha,, India
  • VITAM, Berhampur - 761008, Odisha, India
  • Department of IT, NIT, Durgapur - 713209, West Bengal, India

Abstract


Objective: Developing an efficient computer aided odour detection system for odour classifying and categorizing samples in more efficiency. Methods/Analysis: Among few approaches, the author have proposed the approach for the identification of chemical vapor is to build a cluster of sensors where each cluster will sense a specific chemical. During the experimental analysis, a sensor array consisting of two sensors have been used with an Arduino board and a PC or Laptop. Verification program has been developed in order to verify the system functions. Authors have used MS Visual C++ for developing the computational interface. Findings: Results generated from experiments gives an indication that the developed system was capable of identifying the odors’ of LPG and Alcohol. The developed system shows the intensity of both LPG and Alcohol odour present at certain time. A siren also blows if intensity of any odors’ goes beyond any threshold value. Application/Improvement: If the proposed system uses large number of various type of sensors instead of only two sensors it will shows the intensity of different odors’ present at that time and different sensor’s result do not interfere with each other, that is they are very selective in nature

Keywords

Alcohol Odours, LPG, Odour Detection System, Sensors.

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References


  • Arshak K, Moore E, Lyons GM, Harris J, Clifford S. A review of gas sensors employed in electronic nose applications.Sensor Review. 2004; 24(2):181–98.
  • Sharma S. Implementation of artificial neural network for odor identification using e-nose. National conference on computational instrumentation; Chandigarh. 2010. p.19–20.
  • Di Scala K, Meschino G, Vega-Gálvez A, Vergara J, Roura S, Mascheroni R. Prediction of quality indices during drying of apples using artificial neural networks models for process optimization. International Conference on Food Innovation; 2010. p. 25–9.
  • Brattoli M, De Gennaro G, De Pinto V, Loiotile AD, Lovascio S, Penza M. Odour detection methods: Olfactometry and chemical sensors. Sensors. 2011; 11(5):5290–322.
  • Capelli L, Sironi S, Del Rosso R, Céntola P, Il Grande M.A comparative and critical evaluation of odour assessment methods on a landfill site. Atmospheric Environment.2008; 42(30):7050–8.
  • Nicolas J, Romain A-C, Ledent C. The electronic nose as a warning device of the odour emergence in a compost hall.Sensors and Actuators B: Chemical. 2006; 116(1):95–9.
  • Alphus DW. Diverse applications of electronic-nose technologies in agriculture and forestry. Sensors. 2013; 13(2):2295–348.
  • Dymerski TM, Chmiel TM, Wardencki W. Invited review article: An odor-sensing system powerful technique for foodstuff studies. Review of Scientific Instruments. 2011; 82(11).
  • Röck F, Barsan N, Weimar U. Electronic nose: Current status and future trends. Chemical Reviews. 2008; 108(2):705– 25.
  • Persaud K, Dodd G. Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose. Nature. 1982; 299:352–5.
  • Lewis NS. Comparisons between mammalian and artificial olfaction based on arrays of carbon black-polymer composite vapor detectors. Accounts of Chemical Research.2004; 37(9):663–72.

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