Mining software firm Micromine is set to launch new underground mining precision software that improves loading and haulage processes as part of its fleet management and mine control solution Pitram.

This new AI solution will be released early this year.

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Leveraging computer vision and deep machine learning, on-board cameras are placed on loaders to help track aspects such loading time, hauling time, dumping time and travelling time.

Pitram devices then process the video feeds, and data is transferred to Pitram servers for further processing and analysis.

With this collected information, it is possible to monitor those areas that require potential improvement to boost efficiency of equipment.

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

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“By capturing images and information via video cameras and analysing that information via comprehensive data models, mine managers can make adjustments to optimise performance and efficiency.

“It also provides underground mine managers with increased business knowledge, so they have more control over loading and hauling processes and can make more informed decisions which, in turn, improves safety in underground mining environments.”

“Pitram’s new offering takes loading and haulage automation in underground mines to a new level.”

As part of Micromine’s research and development programme, the company has trialled the technology in Australia, Mongolia and Russia.

The  initial concept was developed in partnership with the University of Western Australia. One of the university’s Master’s students was subsequently recruited by Micromine to help drive the development of machine learning projects across its global business.

Zelina said: “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.”