Leveraging Artificial Intelligence for Enhanced Mining Operations Via-A-Vis Slope Stability Analysis

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized various industries, including mining. The applications of AI and ML in the mining sector, focusing on advancements in image processing, cloud computing, and autonomous systems. This paper highlights the current trends, potential benefits, and challenges associated with implementing AI technologies in mining operations, focusing on image processing, cloud computing, machine learning, deep learning and potential future developments in AI technologies to improve operational efficiency, safety, and decision-making processes in mining. Attempts are made to demonstrate the application of the Machine Learning technique to effectively predict the occurrence of slope failure in typical opencast coal mining area. Specifically, random forest, support vector classifier, and logistic regression algorithms are employed to assess the stability of the slopes. The dataset included in the study uses cohesion, angle of friction, and unit weight of the designed slopes. The performance of the implemented machine learning models for the factor of safety (FOS) prediction is analysed and compared.