Slope failure and debris flow result in several deaths and property losses. Natural disasters, such as landslides and slope failures, result in numerous fatalities and economic losses eachyear. This significant issue prompted the development of an early warning system to reduce accidents, failures, and financial losses. The majority of studies on real-time early warning systems have focused on forecasting unstable locations; however, studies on predicting slope failure occurrence using real-time slope displacement monitoring systems are still lacking and require more investigation. In this paper a three-dimensional displacement sensor, a rain sensor, and a soil moisture sensor, as well as an Internet of Things (IoT), were coupled to monitor slope failure using cutting experiments on a real-scale model slope. The slope movement was monitored in real time in the lab using an integrated, low-cost, efficient, and simple-to-use IoT system. The data was analyzed and the results were explained based on the collected displacement data. This work can be further extended by implementing it in various fields and different industrial applications where slope failures are a part of the production process.
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