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Real-Time AI-Supported Ore Grade Evaluation for Automated Mining - RAGE

The RAGE project will develop automatic and reliable mineral detection based on AI machine learning based on active hyperspectral 3D sensing, indoor positioning, and real-time AI. The currently available mineral deposits are becoming more sparse and less accessible. The battle for resource sufficiency and occupational safety demands for a higher level of automation and higher efficiency of the mining process. This project will deliver automated, reliable, and self-learning mineral mapping by combining active hyperspectral ore grade evaluation with indoor positioning real-time AI-supported software, and data communication solutions for automated mining. These solutions will digitalize the value chain for mining industry.

The RAGE project is a continuation to the Kaivos project, the results of which indicated a great demand for improved data processing and communications. These will be developed into a new level in the RAGE project, together with FGI, VTT, Sensmet, Astrock, Cybercube, Raniot, Outsight, and mines, such as Outokumpu Kemi Mine, who already participated in the Kaivos Project.

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