An intelligent visualization system for landslide monitoring with sensor network

Author(s):  
Wen Chen ◽  
Hongchao Fan ◽  
Tiantian Feng ◽  
Guochao Wu ◽  
Weiyue Li ◽  
...  
IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 8073-8086 ◽  
Author(s):  
Sangseom Jeong ◽  
Junyoung Ko ◽  
Junghwan Kim

Author(s):  
Khaled Rabie ◽  
Vinay Singh ◽  
Vikram Vishal ◽  
Tariq Ansari ◽  
T N Singh

Landslides are a frequent and recurrent problem in hilly regions of India and predicting them is always a challenging task. In this paper, an attempt was made to deal with this problem using advanced physical and numerical modeling methods. Detailed understanding of the initial slope failures is very interesting, and challenging at the same time, in the design and development of wireless sensor network based on early warning of landslide monitoring. A small scale physical model was developed to assess the instability through a sensor network with variable rain fall intensity. This was achieved by increasing the simulated rain water flow intensity in different time spans (dry condition, at t=0 to t= 30 min, 0.5 mm/min at t=30 to t= 60 min, 0.75 mm/min at t=60 to t=91 min and 1 mm/min at t=91 to t= 120 min). The water level and movement in the slope was recorded by rainfall sensor, vibration sensor, soil moisture sensor and a digital camera. The following changes were observed during the slope failure: a) movement of small particles at top of the slope; b) initial failure of medium size soil particle; c) scouring of soil mass; d) whole slope collapse. The obtained results clearly indicated the superiority and effectiveness of the proposed system in providing a factor of safety for the progressive slope.


2015 ◽  
Vol 73 (3) ◽  
Author(s):  
Mohd Amri Md Yunus ◽  
Sallehuddin Ibrahim ◽  
Mohd Taufiq Md Khairi ◽  
Mahdi Faramarzi

In this paper, a wireless sensor network for landslide monitoring (WSNLM) system is described. WSNLM utilized a wireless protocol which is 802.11g. The hardware structure of the WSNLM is discussed where the important parts had been discussed in details. In order to assess the susceptibility of a hill slope to landslide, several parameters had been considered for the network. The important factors that affect landslide is the ground status, which is soil moisture, vibration in the land and also soil temperature. Other factors that can relate to landslide is the environment of the surrounding such as air temperature, humidity and atmospheric pressure. The outputs from the ADXL335 accelerometer were used for slope angle measurement. The output ofa vibration transducer was also used to monitor the hill slope. To account for the susceptibility of the hill slope to the land slide, safety factor value is calculated in real time. The outcomes show that the average moisture content in the soil is around 3 % on a sunny day and the safety factor for a sunny day is around 75. The moisture content in the soil on a rainy day increases tremendously to more than 20 %. At the same time, the safety factor drops to around 70. The system in this paper has the potential to be used as a useful tool for the detection of lanslides.


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