“Our goal is to develop automatic, reliable and self-learning mineral mapping. We seek to reach this goal through active hyperspectral mineral detection, indoor positioning, real-time artificial intelligence and new data transfer methods”, says Sanna Kaasalainen, Head of Department at the Finnish Geospatial Research Institute (FGI).
The project develops solutions to automate and digitalise the mining industry. The RAGE project is a continuation to the earlier Kaivos (Mine) project, led by FGI.
“The Kaivos project revealed a great need for better data processing and data transfer, which the RAGE project seeks to develop further”, Kaasalainen says.
The Kaivos project developed automatic mineral identification and ore classification in the challenging environment of mines. Another important objective was to improve occupational safety by developing new ways to monitor the environment.
In the new RAGE project, VTT Technical Research Centre of Finland is responsible for artificial intelligence research and FGI brings in expertise on positioning. Both parties are involved in developing hyperspectral target detection.
“The project makes use of machine-learning systems for the analysis of the large quantity of data collected with numerous sensors. These systems can be used, for instance, to estimate the composition and ore content of rock material in real time”, says VTT’s Timo Dönsberg, the researcher leading the project.
FGI’s Navigation and Positioning Department is working together with VTT, and the project includes as corporate partners Sensmet, Astrock, Cybercube, Raniot, Outsight and certain mines, such as Outokumpu’s Kemi Mine.
The Real-Time AI-Supported Ore Grade Evaluation for Automated Mining (RAGE) project started on 1 June 2019 and will end on 31 May 2021. The project is funded by Business Finland.
Sanna Kaasalainen, Head of Department, +358 50 369 6806, firstname.lastname@example.org