The Use of Artificial Intelligence and Machine Learning in the Mining Industry


The new technology trends such as machine learning, artificial intelligence, and machine learning all have potential to be very disruptive to existing industries from manufacturing, to agriculture, the medical field, and the retail world. Machine learning also has some interesting and groundbreaking implications for a very old industry, and that is the mining industry. Mining technologies have been well-established and have been around for a long time. The new technologies have the potential to improve yields, cut down on wastage, and improve safety. For these reasons, it is important to explore the possible disruptions that are on the way.

Top Technology Disruptions to the Mining Industry

Mining companies must make use of massive budgets to search the Earth’s crust for precious and valuable elements and ores. These include precious stones and elements such as gold, platinum, and diamond, but it also covers many metals and other substances that are needed for energy and manufacturing. The methods used have been designed and fine-tuned for many years, and there are standard practices available to make sure that mining activities are safe, not too harmful to the local environment, and that they yield desirable benefits.

For a mining company, any improvement that can make their activities more profitable and successful, cut down equipment breakdowns, improve their safety records, and minimize their negative impact on the ground is worth exploring. Artificial intelligence and machine learning are behind a number of improvements that could have far-reaching effects on the way mining is carried out around the world. Here are some of the possible uses of this new technology.

• Autonomous personnel tracking- One of the challenges faced by miners under the ground is having effective communication and tracking systems. When incidents and disasters happen underground, keeping track of everyone’s safety and location becomes the priority concern. With autonomous personnel tracking, it is much easier to track all miners at all times. This system could be facilitated by a network of underground cameras fully active in the mine. This could help supervisors and safety officials keep better watch over who is where and whether or not safety protocol is being adhered to. This proactive monitoring could be used to help improve performance, productivity, and safety of mining operations and teams. It could also be used to pinpoint areas needing improvements.

Another use of such a camera system is as a threat detection system. These cameras could provide real-time awareness of any suspicious activities in and around the mining operations. These could be automatically analyzed and classified by an advanced computer system so that the relevant personnel is immediately notified to investigate the matters further.

• Machine automation and maintenance management- Many large-scale mining operations are very depending on machine operations. If these could be automated better, and through machine learning systems, be better able to handle familiar operations and situations, this could impact productivity in a big way. Underground automation and tracking could improve the efficiency of operators and equipment underground. It could improve safety and ensure that mining equipment is being used optimally.

Mining equipment can be very large and very expensive. Keeping it operating well is important for safety and cost management. Routine maintenance is a requirement that cannot be skipped for these reasons. Machine breakdowns are very undesirable and can affect mining operations in many ways. With machine learning, advanced software systems and data can be used to keep track of each piece of equipment. The operations, functions, and performance of each particular piece of equipment can be better mapped out and tracked so that maintenance schedules can be done as and when needed and any needed repair work can be detected early.

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