Effective monitoring of an air quality network

Raoudha Baklouti, Ahmed Ben Hamida, Majdi Mansouri, Mohamed Faouzi Harkat, Mohamed Nounou, Hazem Nounou

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

1 Citation (Scopus)

Abstract

Air pollution in urban areas could be considered as one of the most dangerous types of pollution that can cause impact health and the ecosystem. Hence, monitoring air quality networks has captivated the interest of various research studies. In this context, this paper deals with Fault Detection of an Air Quality Monitoring Network. The proposed approach is based on nonlinear principal component analysis to cope with modeling of nonlinear data. In addition, the fault detection would be improved by combining exponentially weighted moving average with hypothesis testing technique: generalized likelihood ratio test. The evaluation was carried out on an Air Quality Monitoring Network (AQMN). The results revealed a good results compared to the classical PCA.

Original languageEnglish
Title of host publication2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781538652398
DOIs
Publication statusPublished - 23 May 2018
Event4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018 - Sousse, Tunisia
Duration: 21 Mar 201824 Mar 2018

Other

Other4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
CountryTunisia
CitySousse
Period21/3/1824/3/18

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Keywords

  • Air Quality Monitoring Network
  • Exponentially Weighted Moving Average
  • fault detection
  • Generalized Likelihood Ratio Test
  • Nonlinear principal component analysis

ASJC Scopus subject areas

  • Signal Processing
  • Computer Vision and Pattern Recognition

Cite this

Baklouti, R., Ben Hamida, A., Mansouri, M., Harkat, M. F., Nounou, M., & Nounou, H. (2018). Effective monitoring of an air quality network. In 2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018 (pp. 1-4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ATSIP.2018.8364488