Development of rapid and automated remote sensing methods for ground engagement equipment enabling selective mining

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The mining industry is responding to many challenges (e.g., complex and lower grade ore deposits, tighter environmental regulations) by adopting advanced technologies and increasingly automating mining operations. The operating costs of a mining project can be significantly reduced through the combined implementation of a high-resolution multi-sensor data acquisition system, along with an automated, data-processing system that incorporates analytics-based decision-making solutions. However, the adoption of selective mining systems (enabling cost-effective and sustainable mining operations) has been hampered by limitations in data acquisition and measurement capabilities, with an impact in the robustness of analytics solutions.The main goal of this proposal is to enable selective mining by developing analytics-based decision-makingsolutions based on real-time data acquisition. This will include the acquisition and analysis of high-resolutionhyperspectral and LiDAR data, obtained through ground engagement equipment in an active mine face. The information will be used for characterization of ore hardness; rock fragmentation analysis and discrimination of ore from waste rock. The results of the research will be applicable to a large number of mining operations in Canada and across the world. The project will be conducted in lab scale first, followed by field experiments (in cooperation with industry partner), producing prototype implementations of the analytical solutions, and including extensive testing and validation using real datasets.