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Role Of Computer Vision in the Mining Industry

Updated: Apr 11, 2023

Computer Vision in the Mining Industry

Upgrading the Mining Industry with Visual Artificial Intelligence

The mining industry today, while advanced, is still in need of dire upgrades to its production process. The yield obtained from mining, the techniques used for obtaining the yield, storage, and segregation processes, all can use more efficient technology that can prove beneficial for long term goals. The path to this improvement lies with artificial intelligence, one of the most sought-after technologies today. In artificial intelligence, Computer Vision is that that aims to give machines the ability to see and understand. In fact, this field is becoming increasingly important now that our expectations from modern machinery are rising.

Computer vision applied to mining implements and machines can bring evolution to the mining sector as a whole. A Revamp to mining processes, machinery and instruments are needed in order to increase productivity in the mining sector, especially with the rampantly increasing demand for resources in today’s world. Mining is an industry with lots of capital investment, and hence would benefit greatly from improvements.

Prisma AI’s Computer Vision applications for the Mining Industry

Correct application of Computer Vision and Visual AI-based solutions in the mining industry can lead to a steadfast improvement in overall productivity and yield of resources from mining. Visual AI can be applied to heavy machinery, terrain-related processes, ore segregation and much more. AI algorithms can streamline ore fragmentation assessment, site inspections in open pit mines or underground mines and more. Prisma AI has come up with a suite of Visual AI-based solutions appropriate for the requisite enhancements needed in mining:

Applications of computer vision in mining

Tracking Of Transport Trucks

Geological systems enhanced with machine learning algorithms can track trucks that are transporting raw materials to and from excavation sites, giving proper transit information and ensuring shipments reach their destination on time.

Smart Sorting Of Goods

Intelligent sensor-based solutions will act as a very effective separation and sorting technology, by cleverly sorting out mining materials and ores so they can be picked out from their sorting baskets, making it far easier to access required materials and filter all resources effectively.

Detection Of Safety Equipment

In addition to acting as security surveillance, this computer vision-based system will properly detect if all workers are wearing the standard-issue safety equipment around sites, to enforce safety and security.

And many more similar solutions which can help the mining industry in various processes. Prisma AI is continuously innovating to develop many more helpful products and solutions for the mining sector.

Detection Of Safety Equipment

Intrusion Detection

The system can detect any intruders that are trying to trespass into any restricted areas, especially at night-time. A powerful deterrent for outsiders or such individuals who might be trying to enter into any restricted areas. Any intrusive activities that might be flagged by the system will be reported straight to the concerned authorities so they can catch any would-be intruders.

Incident Detection

Prisma AI’s incident detection system can detect various kinds of incidental activities of any nature, be it a fire, medical emergency such as a worker being hurt, any ruckus or commotion and immediately report it to the concerned authorities, so any incidents can be dealt with in a timely manner.

The Future Of Mining

Mining as a sector has many possibilities for upgradation, in the current world and the coming future. Upgrades will be possible with either application of artificial intelligence, a dominant factor in today’s world, or other upcoming technologies. As mining is an industry of high demand and importance it will stay relevant and will need many upgrades to keep up in today’s technology heavy world.

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