5 Transformational Use Cases of Mining AI

Mining is undoubtedly the backbone of the manufacturing industry - providing the materials needed for the products we use every day.

While the mining industry is clearly essential for producing the transformative tech gadgets coming to market, it has been traditionally slower-moving in regards to implementing new and advanced technologies itself.

However, over the past few years things are starting to shift. The industrial sector is learning that disruptive technologies do not have to completely replace existing systems, and in fact, they can complement them.

The mining sector is undergoing a significant transformation, with artificial intelligence (AI) at the forefront of this change.

Vision AI, also known as computer vision, is revolutionizing various aspects of mining, from exploration and resource discovery to safety and operational efficiency. In this article, we will dive into what vision AI is and how it is revolutionizing AI in mining. We will explore 5 revolutionary use cases of mining AI that are making a significant impact.

AI in mining is here, and it’s here to stay.

What Is Vision AI?

Vision AI (computer vision) is a powerful subsection within the field of AI. It is transformative because it enables cameras to take in and interpret the world around them much like humans do. The neural networks and machine learning algorithms behind vision AI applications allow for real-time insights to be taken from cameras and video footage.

How? Computer vision models are trained to identify and interpret certain objects or events depending on a businesses’ unique use case (e.g. detecting missing PPE gear). After training, an application is built and deployed to edge devices or on the cloud. Businesses can then garner actionable insights, allowing them to target inefficiencies, anomalies, or areas for improvement. These mining AI insights go beyond what employees can manually monitor, saving valuable time and labor.

The Power of Vision AI in Mining

The industrial sector, particularly mining, can largely benefit from vision AI’s real-time data. Why?

Mine sites are notoriously large and difficult to manually monitor around the clock. They are brimming with hazardous areas, dangerous machinery, and unstable terrain. Additionally, their expansive nature and valuable resources make them prime targets for theft. Mine sites have complex processes in-progress at all hours of the day, so managing and ensuring all operations are running smoothly is extremely tedious and time-consuming.

For these reasons, computer vision is not simply a nice-to-have for mine sites, but a necessity.

5 AI Use Cases for the Mining Industry

Now that the significance of vision AI for the mining industry is clear, we can dive into 5 key use cases of the tech. Computer vision delivers unprecedented real-time insights across critical areas like health and safety, site security, environmental monitoring, logistics, and mineral processing. These visual insights are invaluable for boosting site productivity and safety.

1. Hazardous Zone Monitoring

On mine sites, protecting workers' health and safety is paramount. Sites have many potential dangers - from unstable ground to large equipment and machinery. That’s why hazardous zone monitoring is key for preventing potential injuries.

Leveraging alwaysAI’s zone configuration tool, mine operators can map out dangerous and safe zones that can be monitored in real-time. Computer vision enables continuous monitoring 24/7, eliminating the need for manual oversight, which is both tiring and laborious.

Vision AI alerts operators when employees enter accident-prone areas, such as rotating or vibrating equipment, crushers, open stopes, and more. These alerts allow managers to immediately react to protocol breaches - preventing potential issues and protecting the health and safety of workers.

2. Pilfering and Theft Detection

Due to their expansive size and valuable resources, mine sites are often subject to petty pilfering and organized theft. These events can negatively impact the working culture and reputation of the mine.

Luckily, computer vision serves as a second pair of eyes, continuously monitoring the entire mining perimeter for security breaches 24/7 without fatigue. Mining AI can oversee access to restricted, typically-targeted areas, like diesel pumps and scrap metal stores. It can track entry and exit times, vehicle loading, pump usage, vehicle number plates, and more - all in real-time.

Alerts can then be sent to managers for potential theft situations, allowing them to take swift, immediate action if needed. On top of that, visible warning signs about real-time monitoring can further deter illegal activities.

3. Tailings Distribution Tracking

Environmental monitoring is key for protecting both the environmental integrity and health of workers at a mine site. One example? Monitoring the tailings (mining by-products) distribution. Once the valuable fraction of an ore has been extracted, there are tailings left behind that are no longer needed.

Low-probability events like failures in tailings and waste facilities can have significant consequences. For example, if the tailings outlet pipe becomes blocked or misaligned, tailings can accumulate in one area of the pond, compromising the structural integrity of the dam. These events can lead to safety concerns, civil penalties, and even mine closures, making prevention essential. 

Vision AI can alert mine operators of any uneven accumulations within the pond, reducing the risk of dam failure. Computer vision’s real-time monitoring can complement existing tech such as Lidar to further protect the mine’s environment.

4. Ore-To-Ore Pass, Waste-To-Waste Dump Monitoring

Ensuring mine logistics run smoothly is essential for maximizing productivity and efficiency. Oftentimes, when piles of marginal ore are placed near dumps of waste material, mistakes can occur, leading to waste material being mistakenly processed or valuable ore discarded.

In order to protect valuable ore, current cameras can be integrated with vision AI. Zones can be defined for ore and waste piles to ensure the correct loading and routing of haul trucks. If any mistakes are detected, production geologists can immediately begin working to resolve the issue.

5. Conveyor Belt Monitoring

Conveyor belts are at the center of material and metal processing. But unfortunately, they are very prone to mechanical issues and failures that can harm a mine’s productivity. If a belt gets a tear, material can spill and accumulate below the belt, blocking the drive mechanism. Detecting these problems early is key for speeding up repairs and reducing downtime. Vision AI can help.

Cameras integrated with computer vision can monitor belts for tears, slackness, spills, worn-out bearings, and slowdowns in real-time. Vision AI can be integrated with vibration monitors, noise monitors, and infrared cameras for even more detailed monitoring and to ensure the continuous flow of material.

Why Choose alwaysAI’s MineVision Solutions

As the mining industry continues to evolve, AI is proving to be a game-changer. Comprehensive mining AI solutions are at the forefront of this transformation, offering innovative solutions that enhance safety, improve operational efficiency, and drive exploration success. By embracing visual AI technologies, mining companies can gain a competitive edge and navigate the challenges of the future. The collaboration between miners, system integrators, and AI developers will be crucial in unlocking the full potential of AI in mining.

With groundbreaking vision AI solutions, alwaysAI MineVision enables mining companies to optimize operations, boost safety, and drive innovation. The alwaysAI platform combines computer vision and customized analytics to deliver actionable, real-time insights. Check out the rest of alwaysAI’s MineVision solutions here.