Mining Industry Use Cases
Various imaging techniques such as micro-CT, SEM, and optical microscopy are used to analyse the type of processed ore for it's subsequent processing and sale.
Computer vision algorithms can be trained to classify ore types accurately and quickly with far less need for human intervention and at lower error rates
Machinery health monitoring (Industrial - IOT use case)
A large number of diverse mechanical machinery is used in mining operations, from ore processing / crushing equipment, to sorting to transportation (mine trucks and trains). All of this equipment has electrical sensors producing time series sensor data which can be analyzed for signs that a machine needs service, is about to fail, or is operating out-of-specification and thus producing sub-standard resulting output, which affects yield and productivity.
I-IOT algorithms can predict machine health in order to warn of needed equipment maintenance, including for transportation vehicles and infrastructure.
Autonomous vehicles and robotics
Eventually large ore trucks, trains, and other transportation vehicles will be fully autonomous using AI, but in the short term safety enhancements can be added that prevent accidents which affect worker safety and operational costs.
Industrial robotics is advancing via reinforcement learning AI that will eventually replace human-driven or assisted labor in large mining operations.