Mapping active ore faces in real time through hyperspectral imaging
Innovative MRIWA-funded research shows how artificial intelligence can use scanned data to differentiate ore from waste rock
MRIWA research project M0518 uses hyperspectral imaging technology to deliver innovative ore face characterisation.
Developed by Andrew Job from industrial research lab Plotlogic and Professor Ross McAree from the University of Queensland, this system uses visible and infrared light to automatically classify material as ore or waste rock during mining.
This real-time characterisation supports improved mine planning and scheduling today, and could help the autonomous excavators of tomorrow operate in a mine environment.
Hyperspectral imaging delivers real-time mapping of ore faces during excavation, supporting more efficient mine scheduling and paving the way for automation of mine activity.
“Machines equipped with this imaging system would be able to recognise ore grade as they were excavating it” explained Professor McAree.
“Linked to artificial intelligence, this could allow machinery to operate autonomously in the mine environment, removing workers from hazardous parts of the mining process to improve mine safety.”
Read the technical report summarising the findings of this research.
Download the press release.
Page was last reviewed 11 May 2021