Title:AI-Based Rockfall Prediction and Alert System for open pit mines: A Novel Approach using Cyber- physical Systems


Authors:Surabhi Solanki, Tanisha Jain, Praveen Gupta, Vandana Kate


Published in: Volume 3 Issue 1 Jan June 2026, Page No.367-373


Keywords:Cyber-Physical Systems, Rockfall Prediction, Open-Pit Mining, Edge Computing, Cloud Computing, Multiple Sensor Data Fusion, Machine Learning, Artificial Intelligence


Abstract:Rockfalls in open-pit mines are disastrous to personnel safety and can cause catastrophic financial losses by destroying heavy machinery often valued in crores and halting productivity. This paper proposes a comprehensive Cyber-Physical System (CPS) framework for real-time rockfall prediction and alerting. The system integrates multi-source data from geotechnical, geophysical, and environmental sensors. We propose a 4 tiered architecture. Layer 1 extracts data from physical-layer sensors. Layer 2 is edge and cloud layer where collected readings are fed to edge-computing nodes. Layer 3 is Machine Learning layer where to process the data and generate alerts. Our Layer 4 Alert mechanism is also categorized into Low Risk, Moderate Risk and High Risk ensuring accuracy and credibility. Our goal is to implement a multi-tier alert mechanism with human-in-the-loop confirmation that ensures actionable intelligence while minimizing false alarms. This research provides a scalable, open-source framework bridging high-cost commercial systems and accessible CPS solutions for enhanced proactive safety.


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