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AuthorDjelouat, Hamza
AuthorAit Si Ali, Amine
AuthorAmira, Abbes
AuthorBensaali, Faycal
Available date2022-12-29T07:34:44Z
Publication Date2017
Publication NameDigital Signal Processing: A Review Journal
AbstractElectronic nose (EN) systems play a significant role for gas monitoring and identification in gas plants. Using an EN system which consists of an array of sensors provides a high performance. Nevertheless, this performance is bottlenecked by the high system complexity incorporated with the high number of sensors. In this paper a new EN system is proposed using data sets collected from an in-house fabricated 4x4 tin-oxide gas array sensor. The system exploits the theory of compressive sensing (CS) and distributed compressive sensing (DCS) to reduce the storage capacity and power consumption. The obtained results have shown that compressing the transmitted data to 20% of its original size will preserve the information by achieving a high reconstruction quality. Moreover, exploiting DCS will maintain the same reconstruction quality for just 15% of the original size. This high quality of reconstruction is explored for classification using several classifiers such as decision tree (DT), K-nearest neighbour (KNN) and extended nearest neighbour (ENN) along with linear discrimination analysis (LDA) as feature reduction technique. CS-based reconstructed data has achieved a 95% classification accuracy. Furthermore, DCS-based reconstructed data achieved a 98.33% classification accuracy which is the same as using original data without compression. 2016 Elsevier Inc.
SponsorThis paper was made possible by National Priorities Research Program (NPRP) grant No. 5-080-2-028 from the Qatar National Research Fund (a member of Qatar Foundation). Also, we would like to thank Prof. Amine Bermak (Hamad bin Khalifa University, Qatar) for providing the data used in this paper. The statements made herein are solely the responsibility of the authors.
Compressive sensing
Distributed compressive sensing
Gas sensors
Reconstruction algorithms
TitleCompressive sensing based electronic nose platform
Volume Number60

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