Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)

LFG Monitoring Deployment Planning Based on Distributed Compressing Sensing Method

Authors
Qian Zhang, Chuan Huang
Corresponding Author
Qian Zhang
Available Online March 2018.
DOI
10.2991/icaita-18.2018.24How to use a DOI?
Keywords
distributed compressing sensing; monitoring; WSN
Abstract

To minimize the hazard landfill gas (LFG), a monitoring scheme depending on wireless sensors network (WSN) was designed, and information reconstruction was developed to obtain optimal accuracy in the terminal. In this model, the gas-guide area was divided into different clusters. Then, we present an improved joint sparsity model based on distributed compressing sensing method was designed. And compressing sensing system within a sparse measurement matrix and a new wavelet tree model-based adaptive iterative hard thresholding recovery algorithm were also presented. Simulation results show that the scheme can efficiently accomplish monitoring planning.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
Series
Advances in Intelligent Systems Research
Publication Date
March 2018
ISBN
10.2991/icaita-18.2018.24
ISSN
1951-6851
DOI
10.2991/icaita-18.2018.24How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Qian Zhang
AU  - Chuan Huang
PY  - 2018/03
DA  - 2018/03
TI  - LFG Monitoring Deployment Planning Based on Distributed Compressing Sensing Method
BT  - Proceedings of the 2018 2nd International Conference on Artificial Intelligence: Technologies and Applications (ICAITA 2018)
PB  - Atlantis Press
SP  - 93
EP  - 96
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-18.2018.24
DO  - 10.2991/icaita-18.2018.24
ID  - Zhang2018/03
ER  -