Digitalleaf’s RPA Solutions Empowered Hard Hat Detection in Mining Operations

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The latest technological innovation patterns in mining demonstrate a dramatic industry shift towards sustainability. Digital technology works more enthusiastically than ever to provide a genuinely up-to-date, safe, and useful mine that addresses the increased interest for mined materials, while simultaneously surpassing customer expectations and worldwide sustainability initiatives.

Nonetheless, the significance of digital technologies in the mining industry is progressively being recognised as mining organizations are discovering solutions for reducing geological vulnerability, market unpredictability and operational risks.

The Power of Disruptive Technologies

The mining industry is a comprehensive and daunting industry. Depleting ore grades, increasing costs, deficiency of skilled workers, market unpredictability and tough regulatory compliances have been driving the mining business to search for approaches to improve productivity and effectiveness.

Technology here can make a difference. The mining industry has leveraged a plethora of technologies to accelerate business success. Across numerous functions in the mining business, business processes range from a wide variety of rule-based and knowledge-based dreary work, which don’t enhance the core business or to the end-users doing them.

Artificial intelligence and machine learning can help in detecting complicated and deeper deposits by processing vast amounts of data during exploration. The Internet of Things (IoT) can increase productivity of mining operations. Unique identifiers based on radio frequency identification devices (RFID) and sensor technologies automatically transfer and get data over a network without any human intervention. This helps in enhancing traceability and visibility of mining operations as well as automate and improve the operations and maintenance of machines, thereby augmenting human capabilities.

Further, autonomous vehicles have empowered the development of autonomous mines. Autonomous haulage vehicles are equipped with a GPS, vehicle controllers as well as an obstacle detection system that operate without a human, diminish wear and tear on tyres, reduce operating costs and increase mine safety.

One major breakthrough in the field of technology is the development of drones. But, in the mining industry, applications of drones are widespread. Drones are used for stockpile estimation, mine surveying, hot spot detection, inventory management, etc. Moreover, they are also used in hard-to-reach and highly-toxic areas in order to get data-driven insights for mine planning.

Challenges

Given the competitive landscape of the mining business, in addition to the ever-increasing demand for digging, acquiring an economic advantage to guarantee the economic viability of mining operations is currently more significant than ever. While various safety guidelines have been levied in the last 25-30 years, mining remains quite possibly the most dangerous profession for a lot of reasons. The most common danger to diggers working in underground mines is cave-ins. This can happen due to shaft walls, floor breaking, debilitating the larger structure, the steady sinking of land, unstable underground mineshaft ceilings and walls, etc.

A leading mining organization in Canada is a global producer of gold and copper properties. Being a 5,000-strong company, it conducts mining operations in northwestern Quebec and Nunavut, with exploration operations in Sweden, Latin America and the US.

The prospective organization faced a rising number of accidental deaths of workers during mining operations. A major cause was due to workers not wearing hard hats and safety gears. While the organization used drones for safety and surveillance in hazardous areas, the data and footage so collected is daunting and a time-consuming process for a human to gauge and then come up with subsequent steps. The owners are not able to spot any anomalies, which leads to loss of life.

The Internet of Things, robotics, drones, etc. are changing mining into a safer and more productive industry. However, Intelligent Process Automation (IPA) as a solution in this scenario is less explored. For the mining business, IPA can be leveraged to enhance the safety of the workers using automated bots.

For mining organizations to stay competitive, this will require further creative plans and innovations that improve the ability, productivity, and dependability of digging frameworks answerable for detecting, processing, analyzing, and refinement.

Solution

Technologies such as AI, chatbots, IoT, etc. are leveraged to search safety procedures, material safety data sheets(MSDS) while handling hazardous material. Digitalleaf Solutions leveraged Intelligent Process Automation to give an effective solution to this problem. Deploying RPA bots powered by artificial intelligence, Digitalleaf’s approach was to carry out real-time hard hat detection using a machine learning model.

Digitalleaf Solutions assembled CCTV footage data of the mining location. Images captured in the CCTV footage were processed using machine learning-powered object recognition algorithms. Object recognition helps in identifying objects in related digital images.

The model classified and labelled images into two categories – heads and helmets. Digitalleaf Solutions’ RPA bots process the images in real-time, giving necessary outputs to the owner. After processing, the bots create a comprehensive report, which includes details such as mine locations, number of people, number of hats, and compliance percentage. Further, the bots email this report to the owner automatically, notifying them about how many workers are wearing hats. All of this, without any human intervention.

Digitalleaf Solutions leveraged YOLO’s state-of-the-art object detection system. “You Look Only Once” (YOLO) detects objects in an image using Convolutional Neural Networks. An extremely fast and accurate framework, in just a stance, it takes the entire image, predicts the bounding box coordinates and class probabilities for these boxes. Combining Yolo’s single end-to-end model with Digitalleaf’s RPA bots helped the mining organization to experience effective results.

Results

With Digitalleaf’s Intelligent Process Automation solution, the owner could take proactive decisions and notify workers to wear helmets, enhancing the safety of workers by (number) %. Image classification was conducted with 90% accuracy, signalling organization about potential danger. Through IPA, the organization could enable optimized mining conditions and a safer working environment, bringing the number of deaths down to (number)%.

Digitalleaf’s (approach) helped the mining organization to create a safe working environment. With enhanced safety measures in place, mining workers felt more valued. Employees are happier and this gives them more time to work properly and get the job done. All in all, Digitalleaf’s intelligent solution fostered a safe workplace, productivity and mining organization’s brand image.

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