Case studies on IoT monitoring of debris flow and landslides

Aiming at the critical demand for real-time monitoring of slope disasters in mountainous and urbanized regions, this study develops Internet of Things (IoT)-based real-time monitoring systems to resolve the issues of data delay and fragmentation in conventional manual monitoring. Through three engineering cases conducted by the authors, we demonstrate the adaptability of IoT technology in slope disaster monitoring under different instability mechanisms (debris flows and landslides) and geological conditions (artificial-reinforced and semi-natural slopes). Specifically, in Case 1, a novel IoT monitoring system for debris flows integrated with the structural characteristics of rigid barriers is proposed. In Cases 2 and 3, multi-type monitoring sensors and equipment are deployed, including deformation sensors, rainfall gauges and video surveillance devices, to achieve accurate early warnings of rainfall-induced landslides. The novelty of this work lies in proposing a unified IoT architecture scheme applicable to different types of slope disasters. This scheme systematically integrates physico-mechanical sensing devices, a solar-battery collaborative power supply system, video monitoring equipment, data transmission methods, early warning modes, and a cloud-based processing module. Furthermore, the effectiveness of the proposed scheme is validated via successful early warning cases, and this scheme provides an effective technical framework for slope disaster prevention and control.

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Publication Details

Journal
PLoS ONE
Published
2026-11-04
DOI
https://doi.org/10.1371/journal.pone.0361584
Primary Topic
Landslides and related hazards
Type
article
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article

Case studies on IoT monitoring of debris flow and landslides

Lei Huang, Shu-min Wei, Yung-Ming Cheng, Miao-miao Gie
PLoS ONE
Landslides and related hazards
article

Case studies on IoT monitoring of debris flow and landslides

Lei Huang, Shu-min Wei, Yung-Ming Cheng, Miao-miao Gie
article en

Abstract

Aiming at the critical demand for real-time monitoring of slope disasters in mountainous and urbanized regions, this study develops Internet of Things (IoT)-based real-time monitoring systems to resolve the issues of data delay and fragmentation in conventional manual monitoring. Through three engineering cases conducted by the authors, we demonstrate the adaptability of IoT technology in slope disaster monitoring under different instability mechanisms (debris flows and landslides) and geological conditions (artificial-reinforced and semi-natural slopes). Specifically, in Case 1, a novel IoT monitoring system for debris flows integrated with the structural characteristics of rigid barriers is proposed. In Cases 2 and 3, multi-type monitoring sensors and equipment are deployed, including deformation sensors, rainfall gauges and video surveillance devices, to achieve accurate early warnings of rainfall-induced landslides. The novelty of this work lies in proposing a unified IoT architecture scheme applicable to different types of slope disasters. This scheme systematically integrates physico-mechanical sensing devices, a solar-battery collaborative power supply system, video monitoring equipment, data transmission methods, early warning modes, and a cloud-based processing module. Furthermore, the effectiveness of the proposed scheme is validated via successful early warning cases, and this scheme provides an effective technical framework for slope disaster prevention and control.

PLoS ONEVol. 21(11)
Wenzhou University (CN), Taishan University (CN), Sanming University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 12%
Landslides and related hazards
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