Quality Data is the Key to the Successful Adoption of Machine Learning and Artificial Intelligence (AI) in Mining

Mining has a direct or indirect effect on just about every other industry in the world – it provides the raw materials that drive manufacturing, it is the first step in the provision of fuels that power distribution and it has an important role to play in electricity generation. As the saying goes: “if it isn’t grown, it has to be mined”.

Like many other industries, mining has been and will continue to be affected by the rise of machine learning and artificial intelligence (AI). The impact of these is so great that it has been dubbed by some as “The Fourth Industrial Revolution.”

Since the beginning of the industry, mines have always turned to technology solutions to improve performance in areas, such as optimizing productivity; tracking people and equipment; preventing accidents; managing overall equipment efficiency; monitoring instrumentation and sensors, and mapping faces, tunnels and shafts. You name it – every element that impacts the safety or productivity of a mine is somehow being monitored, managed or optimized.

This means that the average, modern mine produces vast volumes of data – data that can be used to power the development and implementation of machine learning and artificial intelligence for use in mines, with improved operational efficiency, better optimized workflows, and improved safety being natural by-products of this process.

Information and data have always played an important role in the mining industry for planning, monitoring, management, and other purposes. It is impossible to run a mine properly without quality data, and as machine learning and artificial intelligence become the norm at most mines, the importance of quality data will become more important than ever before.

To ensure you’re collecting and utilizing quality data at your mining operation, contact Ramjack Technology Solutions. We have everything it takes to monitor, manage and optimize any mine in real-time.