Slope stability monitoring system based on the ORLPStarNET IoT platform

摘要

A promising system for mining industries is deemed as a slope monitoring system (SMS). Additional benefits are possessed by the progression of wireless sensor network (WSN) along with Internet of Things (IoT) for real-time SMS. For observing slope failure (SF) in opencast mines (OCM), a low power, long-range (LoRa), along with an energy-effective solution are suitable. The mine officials along with workers become poorer as they could not have an enhanced smart mine monitoring system owing to severe environmental conditions of mines. For overcoming the existing challenge, a slope stability (SS) monitoring system is created by the work centered on the optimal routing low power star topology networking (ORLPStarNet) IoT platform. Optimal nodes are chosen by the work in a heterogeneous environment utilizing the prediction interval based Woodpecker Mating Algorithm (PI-WMA) technique for avoiding high energy consumption, storage limitation, regular disconnections, and. limited bandwidth to gather the slope data. High throughput is attained with the selection of nodes followed by ORLPStarNet gateway networking. Then, the optimal routing of the path is performed utilizing balanced vector sparrow search algorithm (BVSSA) for data transfer. The problems linked with coverage, routing, cost, and loss of data are overcome by the developed gateway networking. Lastly, the data is saved into the IoT Cloud server. As of the server, the data is accessed by the mine officers, and the SS is monitored by them. For detecting slope collapse, the proposed framework system assists in examining the continual monitoring of the deformation, deformation rate (DR), along with inverse-velocity trends as revealed by the experimental analysis. Concerning throughput, the proposed one stays better when analogized to prevailing methods.