Micromine to advance automation using artificial intelligence

Micromine is launching an underground performance software that bolsters machinery efficiency and safety as part of its Pitram solution in early 2019.

The software will refine loading and haulage processes using computer vision, deep machine learning and onboard cameras placed on loaders to track various variables such as loading time, hauling time, dumping time and travelling empty time.

The video feed is then processed on the Pitram vehicle computer edge device before the extracted information is transferred to Pitram servers for analyses.

Micromine chief technology officer Ivan Zelina said Pitram’s new offering takes loading and haulage automation in underground mines to a new level.

Analysis of images and information that are captured via video cameras will provide underground mine managers with increased business knowledge and control over lauding and haulage processes.

“Mine managers can make adjustments to optimise performance and efficiency … which, in turn, improves safety in underground mining environments,” Zelina said.

“This can contribute significantly to the overall optimisation of underground mines, which we believe have a lot of room for improvement.

“We’re striving to help companies optimise their mining value chain and we believe enhancing one of the most fundamental and critical underground mining assets – loaders – is a great place to start.”

Pitram is a fleet management solution that records, manages and processes mine site data in real-time.

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