Development of IoT-based Wireless Sensor System for Slope Stability Monitoring in Open-cast mines

Abstract

Slope stability in open-cast mines is one of the dominant topics of geological interest. The slopes of open-cast mines need to be monitored consistently so that one has prior knowledge of any slope failure. An early-warning system is necessary for the open-cast mines so that loss of human lives and property is prevented. Both Internet of things (IoT) and wireless sensor system (WSS) have emerged as an aid for real-time monitoring systems. Using WSS, one can monitor the concrete environmental structures by sensing their changes whereas IoT communicates this sensed data from the real-time applications to the application for additional analysis. In real-time monitoring scenarios, power consumption and long-range coverage are of high concern. That is the reason, technologies like WSS, Long Range (LoRa), and IoT have to be collaboratively used to build a slope monitoring system. To monitor slope failure first, slope deformation has to be tracked so that a prediction can be made based on the pattern and generate an alarm that failure is to happen. A coaxial cable along with Time-domain reflectometry (TDR) is used to measure slope deformation based on the reflection principle. This TDR sensor with coaxial cable is set up in slope areas that are more susceptible to failure. Test through open-cast model experiment and shear testing experiment was performed with two types of coaxial cables calibrated with TDR – RG-6 and RG-213 out of which RG-6 was found to be most suitable. Both coaxial cable and TDR are present at the sensing end of the WSS. LoRa acts as a framework for IoT. Since mines are situated in extreme environmental conditions, it is not practical for the mine personnel to be physically present at the mine site to monitor the slopes. The existing slope monitoring systems do not provide the flexibility to monitor slopes independently. Slope monitoring is an exhaustive and risky task for the miners and mine officials if it has to be done physically since any time loss of life may happen due to slope failure. By incorporating LoRa, a wide area is covered and with WSS and IoT slope can be continuously monitored. LoRa operates on various SF out of which SF7 is chosen for this work. This is because, with the increase of SF value, the coverage distance also increases but the signal fades away. The field test results of LoRa with SF7 in open space or non-line of sight (NLoS) areas offered coverage of 2.3 km whereas in the mine site coverage of 1.7 km was obtained without any packet loss. This proved helpful for this research work in open-cast mines because the distance from the mine slope to the mine office is around 1 km. The data which comes from the real-time slope monitoring system has to be processed somewhere so that an early warning can be generated hinting at the occurrence of slope failure. For this purpose, fog computing comes into the picture. Instead of depending on the cloud for every computation, the sensed or monitored data is computed in fog and the outcome is provided to the user. Since the mine environment is uncertain, slope failure can happen within a fraction of a second. For such a scenario, latency-free processing, and delay-free data transmission is required which is offered by fog computing. Besides, it also brings the cloud functionalities nearer to the sensing layer which gives the user the flexibility and eases to use cloud services without any delay. With these motivations and aims, developed and implemented a novel real-time slope monitoring system in this research work is known as Fog-IoT Slope Monitoring (FIoTSM) system to monitor slopes and generate warnings of its failure.