Intelligent Landfill Slope Monitoring System and Data Analysis: Case Study for a Landfill Slope in Shenzhen, China
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 4
Abstract
Efficient and real-time monitoring methods play an important role in the prevention of instability of landfills. A system for long-term monitoring of landfill slope based on the Internet of Things (IoT) was proposed, comprising a perception layer, transfer layer, data layer, platform layer, and user layer. The monitoring system was deployed at the Tiger Pit landfill slope in Shenzhen, China, automatically monitoring surface displacement, settlement, deep displacement, main leachate level, standing leachate level, and rainfall. The monitoring results showed that although the landfill slope was stable, it remained in an active state of movement. The top of the slope experienced significant deformation, and the depth ranging from 0.5 to 8 m exhibited large cumulative deep displacement associated with rainfall. Notably, the standing leachate level at the top of the slope showed pronounced fluctuations. In addition, principal component analysis (PCA) was applied to the monitoring data to reduce dimensionality and identify correlations among the monitored parameters. The surface displacement rate was determined to be a crucial indicator of the landfill slope stability. Auxiliary judging index was introduced, with a threshold set at 0.48355. The proposed monitoring system can provide more reliable, transparent, and timely information regarding the status of the landfill slope, offering significant benefits for real-time slope stability control.
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Data Availability Statement
Data will be made available upon request.
Acknowledgments
The work presented in this paper was jointly supported by the Basic Science Center Program for Multiphase Media Evolution in Hypergravity of the National Natural Science Foundation of China (Grant No. 51988101), the Basic Public Welfare Research Program of Zhejiang Province (Grant No. LGF21E080013), and the National Natural Science Foundation of China (Grant No. 41931289). We would like to gratefully acknowledge laboratory support personnel at the Center for Hypergravity Experimental and Interdisciplinary Research and MOE Key Laboratory of Soft Soils and Geoenvironmental Engineering.
Author contributions: Haoyu Lin: conceptualization, writing–review and editing, supervision, original draft, and resources; Junchao Li: conceptualization, methodology, original draft, project administration, and funding acquisition; Jiwu Lan: conceptualization, writing–review and editing, and supervision; Shijin Dai: conceptualization and data curation; Jianqun Jiang: review and writing–review and editing; and Yunmin Chen: writing–review and editing and data curation.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 4 • December 2024
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© 2024 American Society of Civil Engineers.
History
Received: Mar 21, 2024
Accepted: Jun 25, 2024
Published online: Sep 24, 2024
Published in print: Dec 1, 2024
Discussion open until: Feb 24, 2025
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