Development of an alert system in slope monitoring using wireless sensor networks and cloud computing technique – a laboratory experimentation

Abstract

Opencast mine slope monitoring is crucial to prevent potential failures. Wireless sensor networks (WSNs) offer real-time data collection and analysis for effective slope monitoring to minimises monitoring costs and improves safety. Utilising cost-effective microelectromechanical sensors, slope conditions are wirelessly transmitted using internet of things (IoT), facilitating immediate insights. Monitoring parameters like moisture, vibration, and displacement predict slope behaviour. It is essential to test the sensors before designing and implementing a system for regular monitoring in the field to know the sensor’s performance and match them to the slope condition. The study entails moisture, vibration, and displacement measurements in clay slope models. ZigBee-enabled XBee SC2 modules transmit data to ThingSpeak, triggering PythonAnywhere alerts. As a result, if soil moisture sensor readings were over the predefined threshold value of 50%, an email alert was triggered at the time of the jump. It is concluded that the alert system was developed by using sensors in the clay model developed at a laboratory scale and suitable for field applications on a large scale. © © 2023 Inderscience Enterprises Ltd.