Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living

Muhammad Hassan, Muhammad Umar, Amine Bermak, Amine Ait Si Ali, Abbes Amira

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Recently, ambient assisted living technologies have emerged to improve the quality of life of ageing populations. Identification of health-endangering indoor gases with a hardware-friendly solution may provide an early warning of unhealthy living conditions. Electronic nose technology, using an array of non-selective gas sensors, is a potential candidate to achieve this objective, but state-of-The-Art gas classifiers hinder the development of low-cost and compact solutions. In this paper, we introduce a very simple classifier that transforms the multi-gas identification problem into pair-wise binary classification problems. This classifier is based on the resultant sign of the difference between values of the sensors' features for all possible pairs of sensors in each binary classification problem. A classifier qualification metric is defined to evaluate its suitability with given data of the target gases. As a case study, experimental data of four health-endangering gases, namely, formaldehyde, carbon monoxide, nitrogen dioxide and sulfur dioxide, is acquired in the laboratory by developing an array of commercially available gas sensors fabricated by Figaro Inc. and FIS Inc. A classification accuracy of 94.56% is achieved in distinguishing the target gasses with our proposed classifier. This performance is comparable to that of computation intensive state-of-The-Art gas classifiers despite our classifier's simple implementation.

Original languageEnglish
Title of host publicationISSE 2016 - 2016 International Symposium on Systems Engineering - Proceedings Papers
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509007936
DOIs
Publication statusPublished - 22 Nov 2016
Externally publishedYes
Event2nd Annual IEEE International Symposium on Systems Engineering, ISSE 2016 - Edinburgh, United Kingdom
Duration: 3 Oct 20165 Oct 2016

Other

Other2nd Annual IEEE International Symposium on Systems Engineering, ISSE 2016
CountryUnited Kingdom
CityEdinburgh
Period3/10/165/10/16

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Keywords

  • binary classifiers
  • electronic nose
  • environmental monitoring
  • pair of sensors

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modelling and Simulation

Cite this

Hassan, M., Umar, M., Bermak, A., Ali, A. A. S., & Amira, A. (2016). Computationally efficient environmental monitoring with electronic nose: A potential technology for ambient assisted living. In ISSE 2016 - 2016 International Symposium on Systems Engineering - Proceedings Papers [7753122] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SysEng.2016.7753122