TXT-tool 2.062-1.1: A Landslide Monitoring and Early Warning System

2017 ◽  
pp. 297-308
Author(s):  
Teuku Faisal Fathani ◽  
Dwikorita Karnawati
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Landslide Monitoring ◽  
Monitoring And Early Warning

scholarly journals Research on Submarine landslide monitoring and early warning system

2021 ◽  
Vol 257 ◽  
pp. 03016
Author(s):  
Shanshan Yan ◽  
Liang Xue ◽  
Tianyang Liang ◽  
Yankai Hou ◽  
Hanlu Liu ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Submarine Landslide ◽  
Landslide Monitoring ◽  
In Situ Observation ◽  
Observation Data ◽  
Offshore Platforms ◽  
Submarine Landslides ◽  
Monitoring And Early Warning

Monitoring and early warning of submarine landslides could provide instant predictions for landslides, which is to avoid the destructive damage of submarine facilities such as pipelines and optical cable, etc effectively. However, researches on submarine landslide focus on numerical simulation and laboratory test, lacking support of in-situ observation data. This paper established the submarine landslide monitoring and early warning system by combining real-time monitoring data with web network platform and database technique. Based on the computational analysis of key monitoring parameters in the process of seabed deformation and sliding, the system has realized the accurate prediction and early warning of submarine landslides. The system has been applied to the submarine landslide monitoring in Zhoushan sea area, Zhejiang province, China, which has ensured the safety of offshore platforms and submarine projects in this area. The establishment of this system provides a new idea and method for submarine landslide warning.

scholarly journals Scale‐oriented landslide monitoring and early warning system for uranium legacy complexes in Mailuu Suu, Kyrgyzstan

2021 ◽  
Vol 14 (1) ◽  
pp. 47-53
Author(s):  
Markus Keuschnig ◽  
Andreas Schober ◽  
Robert Delleske ◽  
Katharina Brandner ◽  
Giorgio Höfer‐Öllinger
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Landslide Monitoring ◽  
Monitoring And Early Warning

scholarly journals 5G IoT-based Geohazard Monitoring and Early Warning System and its Application

2021 ◽  
Author(s):  
Zhaohua Li ◽  
Dawei Liu ◽  
Xiaokun Sun ◽  
Wang Peng
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Surface Deformation ◽  
Warning System ◽  
Slope Instability ◽  
Landslide Monitoring ◽  
Point Distribution ◽  
Geological Disasters ◽  
Stability Of Slopes ◽  
Monitoring And Early Warning

Abstract With the expansion of human production activities, geological disasters caused by slope instability are occuring more frequently. Hence, the research on effective monitoring and forecasting of the geotechnical stability of slopes is of great significance for the prevention and mitigation of slope geological disasters. In this study, a landslide monitoring and early warning system based on 5G Internet of Things (IoT) technology is introduced. The system monitors important indicators such as three-dimensional surface displacement, rainfall, and ground cracks using Global Navigation Satellite System (GNSS) equipment and various IoT sensors deployed on site. The key monitoring data are transmitted and displayed by 5G communication and advanced data visualization technologies. An early warning guideline is established by combining the surface deformation rate-time curve according to a four-level early warning method as well as embedded vector maps such as the topographic and geomorphological remote sensing map of the monitoring area, the geological section map, and the monitoring point distribution map. The system has the functions of accurate acquisition, rapid transmission, automatic search, and comprehensive analysis, and is applied to the study of creep slopes of the Lianhe terraces in Youxi County, Fujian Province, with remarkable results.

scholarly journals 5G IoT-based geohazard monitoring and early warning system and its application

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Zhaohua Li ◽  
Linquan Fang ◽  
Xiaokun Sun ◽  
Wang Peng
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Surface Deformation ◽  
Warning System ◽  
Slope Instability ◽  
Landslide Monitoring ◽  
Point Distribution ◽  
Geological Disasters ◽  
Stability Of Slopes ◽  
Monitoring And Early Warning

AbstractWith the expansion of human production activities, geological disasters caused by slope instability are occurring more frequently. Hence, the research on effective monitoring and forecasting of the geotechnical stability of slopes is of great significance for the prevention and mitigation of slope geological disasters. In this study, a landslide monitoring and early warning system based on 5G Internet of Things (IoT) technology is introduced. The system monitors important indicators such as three-dimensional surface displacement, rainfall, and ground cracks using Global Navigation Satellite System equipment and various IoT sensors deployed on site. The key monitoring data are transmitted and displayed by 5G communication and advanced data visualization technologies. An early warning guideline is established by combining the surface deformation rate–time curve according to a four-level early warning method as well as embedded vector maps such as the topographic and geomorphological remote sensing map of the monitoring area, the geological section map, and the monitoring point distribution map. The system has the functions of accurate acquisition, rapid transmission, automatic search, and comprehensive analysis and is applied to the study of creep slopes of the Lianhe terraces in Youxi County, Fujian Province, with remarkable results.

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