The progressive deepening of mining activities and the global pursuit of low-carbon energy systems have converged to position mines not only as sites of resource extraction but also as complex subsurface energy systems. In recent decades, increasing attention has been directed toward understanding geothermal energy extraction from mines, the coupled thermal–hydraulic–mechanical behavior of fractured rock masses, and the integration of heat management with mine safety and sustainability. This study develops a comprehensive, publication-ready synthesis and original analytical framework grounded strictly in recent and foundational literature on mine geothermal systems, underground heat transfer, backfill-based thermal storage, enhanced geothermal systems, fracture evolution, and in situ subsurface investigation technologies. Drawing on numerical modeling studies, case-based analyses, and theoretical advancements reported across mining science, geothermal engineering, and deep Earth exploration research, the article systematically elaborates on life-cycle thermal responses of mine geothermal systems, the role of groundwater flow, fracture evolution, non-Darcy flow effects, and the synergetic design of geothermal wells and backfill heat exchangers. Special emphasis is placed on how geological controls, mining-induced structural evolution, and engineered interventions such as phase-change heat storage backfill and multi-branch geothermal wells collectively influence energy extraction efficiency and thermal hazard mitigation. The methodological approach integrates conceptual modeling, numerical simulation paradigms, and interpretative analysis of reported case studies, avoiding mathematical formalism while offering deep theoretical interpretation. Results are discussed in terms of emergent patterns across different geological and operational contexts, highlighting how heat transfer pathways evolve dynamically with mining progression and backfill deployment. The discussion critically evaluates limitations in current modeling assumptions, scale effects, and uncertainties related to fracture characterization, while also connecting mine geothermal research with broader developments in deep Earth coring, gas hydrate exploration, and subsurface energy storage. By synthesizing these domains, the article advances a holistic perspective on mines as engineered geothermal systems embedded within complex geological environments. The findings contribute to both academic understanding and practical design strategies for sustainable energy recovery, mine safety enhancement, and the long-term utilization of deep subsurface space.

The mining industry has entered a decisive period of technological transformation driven by the convergence of automation, robotics, sensing, and artificial intelligence. Across both surface and underground operations, autonomous and semi-autonomous systems are increasingly deployed to address long-standing challenges related to worker safety, operational efficiency, productivity variability, and environmental constraints. Despite significant technical progress, the implementation of automation in mining remains uneven, constrained not only by engineering limitations but also by systemic safety risks, human–machine interaction challenges, and the complexity of integrating autonomous systems into legacy mining environments. This research article presents a comprehensive, theory-driven examination of autonomous and robotic systems in mining, synthesizing contemporary developments in unmanned aerial vehicles, unmanned ground vehicles, longwall automation, computer-vision-based collision avoidance, and sensing technologies within a unified systems engineering and human-systems integration framework.

Methodologically, the study adopts a structured qualitative synthesis approach grounded in systems engineering principles, functional safety doctrine, and human-systems integration theory. Findings reveal that productivity gains and safety improvements are most pronounced when automation is embedded within a coherent safety lifecycle that incorporates functional safety standards, human-centered design, and continuous risk assessment. Conversely, failures in mining automation frequently stem from inadequate integration of sensing, control, and human oversight rather than from deficiencies in autonomy algorithms alone.

The discussion critically interrogates prevailing assumptions surrounding full autonomy, highlighting limitations related to trust calibration, situational awareness degradation, and regulatory ambiguity. The article concludes by proposing future research and implementation pathways that emphasize adaptive autonomy, resilient sensing architectures, and the formal integration of human-systems integration into mining automation governance. By reframing automation as a socio-technical safety system rather than a discrete technological artifact, this research contributes a foundational perspective for safer, more sustainable mining operations in the coming decades.