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AI Based Rockfall Prediction and Alert System for Open-Pit Mines

Nutan P. Dalal,
nutandalal17@gmail.com
Shreyash V. Kawale,
shreyashkawale41@gmail.com
Dr. M. V. Lande,
milind.jdiet@gmail.com
Prathviraj G. Wadkar,
wadkarprathviraj@gmail.com
Nikita S. Mistri,
nikimistri711@gmail.com
Department of Computer Engineering Government Polytechnic Gadchiroli, Maharashtra , India

Abstract - This project presents the design and implementation of an AI-based rockfall prediction and alert system for open-pit mines using Drone technology. The system uses a Drone equipped with environmental sensors such as temperature, moisture, vibration, and pressure sensors to collect real-time environmental data from mining areas. The collected data is transmitted wirelessly to a monitoring system using an ESP32 microcontroller. The system continuously monitors environmental conditions and analyzes sensor data to identify abnormal changes that may indicate slope instability or potential rockfall events. Parameters such as sudden increases in vibration, excessive moisture levels,and abnormal pressure variations are used as indicators of  possible rock movement.When the system detects unsafe conditions beyond predefined threshold values, an automated alert mechanism is activated. The alert system includes buzzer alarms and warning notifications toinform workers and supervisors about potential hazards.  This solution provides a real-time monitoring and early warningsystem that helps improve worker safety and reduce accidents in open-pit mining environments. The proposed system offers a cost effective and reliable approach for monitoring hazardous mining zones using sensor technology and automated alert mechanisms