Mining is one of the important earing sources in many countries across the globe. In fact, many industries worldwide rely heavily on the supply of mineral commodities from underground. As a result, the mining industry plays a pivotal role in the world’s economy. Statistics shows that, the revenue of the top 40 global mining companies (who form the vast majority of the whole mining industry) accounted for around 656$ billion in the year 2020. According to International Council on Mining & Metals (ICMM), Australia and South Korea are the top most countries dependent on mining. It further reports that, of the top 70 countries dependent on mining, 63 are low-income countries that stand to expand their national economies via. investments, exports, taxes and employment related to mining.
Despite its importance and significant contribution to the world economy, mining continues to remain one of the most hazardous occupations all over the world. The underground coal mines are especially notorious owing to their high rates of accidents. According to the National Institute for Occupational Safety and Health (NIOSH), 95% of the non-fatal injuries are incurred to surface mine workers. Moreover, powered haulage related accidents are predominant in mines. Thus, safety in mining industry continues to remain a matter of contention to all related to the industry.
Also Read: How AI-based Visual Inspections and Quality Control Can Prevent Anomalies in Manufacturing Plant?
However, AI and its subsidiaries like video analytics have great potentialities to mitigate the safety issues prevailing in the mining industry. This blog thus, attempts at discussing the various ways how AI can ensure safer operations and risk management in mining industry.
What are the Common Safety Hazards Prevailing in the Mining Industry?
The mining industry has the reputation of ‘a risky business’. Health risks in the mining industry are diverse and are often quite serious in nature. It is thus, required for the miners to protect themselves accordingly. Although significant steps have been taken to control occupational health hazards, yet there remains scope of further risk mitigation.
Some of the commonly occurring safety hazards in the mining industry are:
How can AI ensure Safety in Mining Industry?
AI and its subsidiaries have the potentiality to significantly contribute towards ensuring mining safety as they can help initiate immediate actions to prevent injuries in the following ways:
Powered Haulage Accidents Prevention: Powered haulage equipment like scoops, front end loaders, shuttle cars, locomotives and the like are a common sight in mines. According to the reports of Mine Safety & Health Administration (MSHA), 46.3% of accidents in the mining sites are caused due to powered haulage equipment. However, such accidents can be prevented using adequate surveillance and safety monitoring technologies. This is where AI comes in! Using the power of AI video analytics enables stakeholders to have human-vehicle collision alerts, detect operator’s distraction, manage on-road fleet in real-time, and much more. All this in turn facilitates effective mining fleet management that helps prevent accidents caused by vehicle collisions.
Fire & Smoke Detection: Statistics reveal that 55% of gas explosions occur in coal mines. Thus, fire & explosions possess a constant threat to the lives of the miners and also to the productivity in mines. Electrical energy sources, hot surfaces and frictional heat, and open flames from cutting & welding tools are often cited as common causes of fire accidents in mines. However, by leveraging the power of AI and vision intelligence it is possible to prevent catastrophic fire accidents in mines as it allows instant fire and smoke detection, real-time fire alerts, extreme temperature alerts and the like.
Work at Height Safety Monitoring: As per the reports by Centers for Disease Control & Prevention (CDC), fall from height (FFH) is the second biggest cause of non-fatal injuries in the mines. Slips while climbing uneven rocks, trips while walking on uneven roads, free falls into ruts and holes are some of the primary causes of fall from height in mines. However, with AI video analytics for work at height safety monitoring, stakeholders can have a fall prevention plan (FPP) as it helps detect missing life safety ropes, improper climbing methods used by workers, detect missing barrier/ improper barrier, gondola/ suspended platform monitoring and the like.
Confined Space Work Safety Monitoring: The BLS Occupational Injury and Illness Classification System (OIICS) reports that 60% of fatal injuries in mines occur during underground mining & tunneling operations. Falling rocks, fires & explosions, and asphyxiation constitutes the major causes of confined space deaths in mines. However, AI can facilitate confined space safety monitoring by alerting high temperature within confined spaces, danger zone intrusion, falling objects and the like. It can thus mitigate the various safety challenges prevailing in confined space working.
PPE Detection: PPE is a basic necessity for ensuring workers’ safety in jobsites. Hard hats, safety glasses, mask/respiratory protection, hearing protection, reflective jackets, lifesaving ropes and the like are some of the important PPEs used for mining. AI powered cameras are capable of detecting whether or not workers are wearing (proper) PPE. Thus, PPE detection with AI can further boost safety in the mining jobsites.
How viAct can help?
Looking into the increasing number of safety hazards in the mining jobsites, viAct is now introducing its proprietary scenario-based AI video analytics solutions for mining industry. After several successful deployments of its various construction safety solutions , AI video analytics for oil & gas industry, and AI solutions for manufacturing industry; viAct is now driving value from data using scenario-based AI powered video analytics for critical mining sites to optimize processes, enhance decision-making and improve safety.
Its automated monitoring system provides round-the-clock surveillance of the mines. The real-time data from video analytics is used to reduce mining fatalities. Further, the automated navigation system facilitates better and faster decisions – critical to improve the health & safety of the frontline mine workers. It also helps in reducing their exposure to critical/dangerous working situations; thus, transforming the traditionally process-oriented mining industry into a people-oriented one.
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