TY - GEN
T1 - Towards an Integrated Framework for Fugitive Methane Source Localization and Monitoring in a Wireless Sensor Network
AU - Jawhari, Amira Al
AU - Souissi, Yasmine
AU - Ghommam, Jawhar
AU - Jamoussi, Yassine
AU - Mnif, Faisal
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Gas leaks are the main cause of industrial fires and accidents. These cause countless fatalities, equipment damage, and other severe environmental effects. In this paper, we provide a framework for the monitoring and detection of methane leakage using a diffusion model based on the gas diffusion theory. Given that centralized Least Square methods are not efficient and robust as they require the gathering and processing of large-scale measurements on a central node. We propose a detection technique which makes use of the distributed (Non-linear) least squares method to overcome this problem. Then, a network of connected methane sensors is used to detect gas leaks. In order to estimate the parameters of the diffusive model for the gas leakage on each sensor node, a distributed recursive estimator of the consensus plus an innovation type technique is used. The characteristics being estimated include the gas source's distance, which will be effectively triangulated to determine the source's precise location. The targeted location is subsequently estimated using a location dispersed algorithm-based LS.
AB - Gas leaks are the main cause of industrial fires and accidents. These cause countless fatalities, equipment damage, and other severe environmental effects. In this paper, we provide a framework for the monitoring and detection of methane leakage using a diffusion model based on the gas diffusion theory. Given that centralized Least Square methods are not efficient and robust as they require the gathering and processing of large-scale measurements on a central node. We propose a detection technique which makes use of the distributed (Non-linear) least squares method to overcome this problem. Then, a network of connected methane sensors is used to detect gas leaks. In order to estimate the parameters of the diffusive model for the gas leakage on each sensor node, a distributed recursive estimator of the consensus plus an innovation type technique is used. The characteristics being estimated include the gas source's distance, which will be effectively triangulated to determine the source's precise location. The targeted location is subsequently estimated using a location dispersed algorithm-based LS.
KW - distributed detection
KW - gas leak detection and localisation
KW - industrial wireless
KW - Methane
KW - nonlinear least square method
KW - source localization
KW - wireless sensor networks (WSNs)
UR - http://www.scopus.com/inward/record.url?scp=85185838632&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85185838632&partnerID=8YFLogxK
U2 - 10.1109/SSD58187.2023.10411323
DO - 10.1109/SSD58187.2023.10411323
M3 - Conference contribution
AN - SCOPUS:85185838632
T3 - 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
SP - 728
EP - 733
BT - 2023 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th International Multi-Conference on Systems, Signals and Devices, SSD 2023
Y2 - 20 February 2023 through 23 February 2023
ER -