Gas identification with spike codes in wireless electronic nose: A potential application for smart green buildings

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Recently, building related illness and sick building syndrome have appeared as growing concerns for building residents. Ambient assisted solutions can be opted for in monitoring air quality in indoor environments by rapidly identifying health endangering gases. Industrial solutions are not appropriate for such a purpose because these incur high cost and long analysis time. In this paper, we present a wireless electronic nose system, containing commercially available gas sensors, to identify toxic gases in the indoor environment. Rapid identification with a reduced computational power and memory requirement is the major challenge to adopting a wireless electronic nose as an ambient assisted solution. Recently, logarithmic time encoding model based spike latency coding schemes have been used for hardware friendly implementation. However, these involve regression operation and a large memory requirement. In this paper, we use transient features to form spike codes instead of the logarithmic time encoding model, and as a result, we not only eliminate the requirement of regression but also achieve rapid identification with reduced memory size. A confidence coefficient is defined to examine the correctness of our approach, and if its value is below a certain threshold then a new sample can be collected for the classification decision. As a case study, data of five gases, namely carbon dioxide, chlorine, nitrogen dioxide, propane, and sulphur dioxide, is acquired in the laboratory environment and used to evaluate the performance of our approach.

Original languageEnglish
Title of host publicationIntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference
PublisherIEEE
Pages457-462
Number of pages6
ISBN (Electronic)9781467376068
DOIs
Publication statusPublished - 18 Dec 2015
EventSAI Intelligent Systems Conference, IntelliSys 2015 - London, United Kingdom
Duration: 10 Nov 201511 Nov 2015

Conference

ConferenceSAI Intelligent Systems Conference, IntelliSys 2015
CountryUnited Kingdom
CityLondon
Period10/11/1511/11/15

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