TY - GEN
T1 - Effective monitoring of an air quality network
AU - Baklouti, Raoudha
AU - Ben Hamida, Ahmed
AU - Mansouri, Majdi
AU - Harkat, Mohamed Faouzi
AU - Nounou, Mohamed
AU - Nounou, Hazem
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/5/23
Y1 - 2018/5/23
N2 - 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.
AB - 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.
KW - Air Quality Monitoring Network
KW - Exponentially Weighted Moving Average
KW - Generalized Likelihood Ratio Test
KW - Nonlinear principal component analysis
KW - fault detection
UR - http://www.scopus.com/inward/record.url?scp=85048506531&partnerID=8YFLogxK
U2 - 10.1109/ATSIP.2018.8364488
DO - 10.1109/ATSIP.2018.8364488
M3 - Conference contribution
AN - SCOPUS:85048506531
T3 - 2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
SP - 1
EP - 4
BT - 2018 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on Advanced Technologies for Signal and Image Processing, ATSIP 2018
Y2 - 21 March 2018 through 24 March 2018
ER -