Connected Futures Series
Based on an interview between Hélène Gey, Axceta’s CMO and Alain Beauséjour, The MISA Group General Manager
The mining industry is transforming profoundly, driven by the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT). As mines become increasingly digitized, connected technologies optimize operations, improve safety, and drive sustainability.
In this second article of the Connected Futures series, we explore how AI and IoT reshape mining, from predictive maintenance and real-time monitoring to autonomous systems and environmental impact management.
The Next Big Shift: From Digital Transition to Autonomous Mining
Mining’s digital transformation is well underway. Mine 4.0 emerged in 2017, focusing on automation and connectivity. By 2019, the industry shifted toward the autonomous mine, a vision built on real-time data, AI-driven analytics, and connected equipment.
A key breakthrough came when Agnico Eagle successfully implemented LTE-based data transport for underground mining. This milestone demonstrated that robust digital networks could support real-time IoT applications, unlocking new efficiencies and safety measures.
With underground mines now equipped to transmit data, mining companies can connect everything—from human operators to mobile and fixed equipment—enabling real-time analytics, predictive maintenance, and automation. However, this digital shift also presents challenges, particularly in data management and cybersecurity. As connectivity grows, companies must implement best data collection, storage, security, and quality control practices to fully leverage AI-driven insights.
Predictive Maintenance: Reducing Downtime with AI & IoT
Traditional mine operations followed a fixed cycle: work teams would receive their tasks in the morning, head underground, complete their work, and report back. This process, while effective, was slow and reactive.
With AI and IoT, equipment monitoring has become immediate. Sensors collect real-time operational data, allowing companies to:
- Detect mechanical issues before failure occurs.
- Optimize maintenance schedules to minimize downtime.
- Reduce overall costs by preventing unexpected breakdowns.
For example, predictive analytics can forecast equipment malfunctions, enabling proactive repairs. This shift from reactive to preventive maintenance improves operational efficiency and extends the lifespan of mining assets.
Enhancing Worker Safety: AI-Driven Risk Management
Mining presents significant safety challenges, particularly in underground environments. AI and IoT play a critical role in hazard detection and risk mitigation.
In surface mining, autonomous haul trucks and proximity detection systems have enhanced safety. In Australia, for instance, self-driving trucks operate with near-zero accidents due to advanced AI-driven collision avoidance.
In underground mining, challenges remain. Constrained environments require robust connectivity and AI-enhanced detection systems to ensure safety. Leading initiatives include:
- Proximity Detection for Teleoperated Vehicles: Companies are testing AI-powered proximity sensors to prevent collisions.
- Automated Emergency Response: AI can analyze sensor data to detect structural instability, gas leaks, or hazardous conditions, triggering real-time alerts.
The industry remains cautious, ensuring that no digital technology is implemented at the expense of worker safety. AI adoption in underground mining is progressing through controlled testing and gradual deployment.
The Road to Fully Autonomous Mines
Since 2019, experts have predicted that autonomous mines will emerge between 2030 and 2035. However, the timeline remains uncertain, as mining presents unique challenges:
- Every mine is different: Unlike industries with standardized environments, mines vary in geology, depth, and logistical constraints.
- Capital investment decisions depend on mine lifespan: A mine with only 2 years of remaining reserves may not justify full-scale automation.
- Technology maturity is still evolving: AI, robotics, and teleoperation systems must undergo extensive testing before wide adoption.
Despite these challenges, the path to autonomous mining is clear. Companies are gradually assembling the puzzle pieces, and each new AI or IoT application adds to the industry’s understanding of what a fully autonomous operation will look like.
AI & IoT in Sustainable Mining: Managing Environmental Impact
Sustainability is becoming a significant focus for mining companies, and AI-driven data analytics is revolutionizing environmental monitoring.
Air and Water Quality Management:
- IoT sensors track air pollution and water quality in real time.
- AI analyzes historical data to predict environmental risks and optimize mitigation strategies.
Digital Twins for Mine Planning:
- Virtual models of mines allow companies to simulate environmental impact before beginning extraction.
- This enables better restoration planning and regulatory compliance.
Energy Optimization:
- AI helps balance power consumption, reducing peak energy loads and improving efficiency.
- Mines are adopting renewable energy sources, such as wind and solar, where feasible.
- Battery storage solutions help manage energy supply fluctuations.
By leveraging digital technologies, mining companies can meet environmental regulations, enhance operational efficiency, and improve their social license to operate.
Supply Chain Transparency: Blockchain & IoT in Mineral Traceability
The demand for ethically sourced materials is rising, particularly for critical minerals like lithium, nickel, and copper used in EV batteries. AI and IoT are enabling greater supply chain transparency:
- Blockchain-based tracking systems ensure that minerals are sourced responsibly.
- AI verifies compliance with environmental and labor regulations.
- Companies like Propulsion Québec are piloting traceability solutions to guarantee that Quebec’s mining industry remains competitive.
Combining IoT for real-time tracking and blockchain for data integrity ensures a transparent and responsible supply chain.
The Future of AI and IoT in Mining
In 2025, the mining industry will already witness significant breakthroughs in AI and IoT adoption:
- Real-time mineral analysis and data collection will become the standard, enabling predictive geological modelling.
- Automation will expand beyond haul trucks, with AI-driven drills and exploration tools gaining traction.
- Digital twins will revolutionize mine design and planning, improving operational efficiency and reducing risk.
Mining is well into the new digital era, and AI and IoT are at the forefront of this transformation. While challenges remain, the industry is moving steadily toward autonomy, efficiency, and sustainability.
Stay tuned for the next article in Axceta’s Connected Futures series, where we’ll explore AI and IoT’s role in another industry shaping the future of technology.
