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.

Contact persons
Funding organisation or partners
FGI
Tekes