SmartMin’s Machine Learning technology at Mandela Mining Symposium

Machine Learning in Mining and Geology

SmartMin’s Machine Learning technology at Mandela Mining Symposium

SmartMin’s work featured in the Mandela Mining Precinct Symposium.

In June, some of the work that we have been doing in machine learning with regards to its application in mining was on display at the symposium.

The presentation detailed how machine learning can be applied to sub-surface geological and geophysical decision-making.

Machine Learning in Mining and Geology

With the world being in an era where data is available in large volumes, we have an opportunity to aid fundamental analytical practices with the use of technologies that can give us insights beyond what a humans can gather.

With the advent of modern seismic processing techniques and computing power, we are now able to extract key features for geological structures, and added with machine learning, we can use extract insights into geology that allow for the prediction of metal concentrations.

This new approach allows mines to plan ahead, knowing where they will find geological structures, as well as it’s dimensions and other physical characteristics.

These tools are part of the pioneering technologies for the application of big data and artificial intelligence in the mining industry. SmartMin is the first artificial intelligence company in South Africa with specifically tailored solutions for the mining industry due to our background in mining and in the geosciences. Our team consists of the leading experts for machine learning in mining and geology.

This presentation was delivered as part of the Advanced Orebody Knowledge Programme which is run by the Mandela Mining Precinct. The Mandela Mining Precinct is a Public-Private Partnership between the Department of Science and Innovation (DSI) and the Minerals Council of South Africa. It is an initiative aimed at revitalising mining research, development and innovation in South Africa to ensure the sustainability of the industry.

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