A Large Scale Model Test on Detection of Potential Risk of Slope Failure by Monitoring of Shear Strain in Shallow Section

A Study on the Slope Failure Monitoring of a Model Slope by the Application of a Displacement Sensor

“…In order to receive and analyse signals from the sensors, a method using a data logger connected through a wire to monitor the collected signals on a PC via a USB cable is typical [27,28,30]. However, this method has limitations in collecting data over a long period of time, and if the area to be observed is wide, a large number of data loggers are required, which is costly and requires significant manpower.…”

“…However, this method has limitations in collecting data over a long period of time, and if the area to be observed is wide, a large number of data loggers are required, which is costly and requires significant manpower. Therefore, in this study, we have upgraded the warning system developed by Tamate et al [27,28,30] into a slope monitoring system using the Internet of Things (IoT). The monitoring system, proposed in this study, in which displacement sensors is combined with IoT, is more efficient and easy to monitor slope failure compared to the previous method proposed by Tamate et al The warning system suggested by the previous studies was able to alert the slope failure only, but the upgraded monitoring system, proposed in this study, can send the slope movement data to the server in real-time through a wireless LoRa network, analyse the received data, and send the slope failure alert to users' smartphones.…”

“…Voight [32] proposed a method of estimating the slope failure time using the inverse slope displacement and displacement velocity over time. Likewise, Tamate et al [27][28][29][30] studied the relationship between the risk of slope failure and increase in the shear strain in the shallow slope surface. The previous studies by Tamate et al [28][29][30] used the inverse of shear strain for the prediction of slope failure, whereas, in this study, the inverse of slope displacement has been considered for monitoring slope failure.…”

“…Likewise, Tamate et al [27][28][29][30] studied the relationship between the risk of slope failure and increase in the shear strain in the shallow slope surface. The previous studies by Tamate et al [28][29][30] used the inverse of shear strain for the prediction of slope failure, whereas, in this study, the inverse of slope displacement has been considered for monitoring slope failure. This study was performed to analyse the slope failure behaviour using inverse displacement (1/displacement) over time via the analytical method mentioned above.…”

“…This increases the life and efficiency of the warning system, with less need for maintenance. Moreover, the warning system proposed by the previous studies [27][28][29][30] was targeted to raise alarm before the slope failure. But the warning system, proposed in this study, is able to receive the slope movement data in real time via a wireless LoRa network and analyse it.…”