1921 Such cross-discipline exchange accelerates technology progression (Figure 5) and the development of novel sensing and monitoring technologies. Indeed, the development of multi-sensor based, high degree of freedom tracking for the aerospace industry has provided insights into improving precision of slope deformation and rock fall trajectory tracking. Further, stereo–depth fusion pipelines improved for aerospace applications are now being applied to underground mining for mine equipment condition monitoring (Sun et. al., 2023). The space program’s emphasis on compact, power‑efficient payloads further supports development of ruggedized sensing (e.g. modular platforms deployable in underground applications). Figure 5 – Technology progression, from geotechnical to aerospace showing original Sirovision photogrammetry and geotechnical mapping technology for underground and surface mining (two left most images), progression to application of novel 3D vision technologies for aerospace manufacturing (central image) and finally, MRS payload development and launch to ISS (right two images). 4. FUTURE TRENDS The next decade will see geotechnical monitoring evolve from discrete sensing systems into fully integrated, intelligent networks that underpin autonomous mining operations. Artificial Intelligence (AI) will play a pivotal role in this transformation, enabling real-time interpretation of multi-modal data streams from radar, vision, distributed fibre optic sensing (DFOS) and a multitude of traditional geotechnical sensors. AIdriven analytics will support predictive hazard detection, dynamic risk assessment, and adaptive control strategies for slope stability and rockfall mitigation. Machine learning models will also facilitate sensor fusion at scale, reducing false positives and improving situational awareness for both human operators and autonomous agents. Silicon photonics is poised to revolutionize DFOS deployment by miniaturizing and costoptimizing interrogator units. Photonic integrated circuits will replace bulky optical components, delivering compact, energy-efficient systems capable of supporting kilometre-scale sensing networks. This advance will enable widespread adoption of DFOS for continuous strain, temperature, and acoustic monitoring in both surface and underground environments, bridging the gap between laboratory prototypes and rugged mine-ready solutions. Looking further ahead, quantum technologies promise breakthroughs in sensing and computation. Quantum gravimetric sensors could provide ultra-precise subsurface imaging, revealing geological structures and stress fields beyond the reach of conventional methods. In parallel, quantum computing offers unprecedented capacity for simulating complex rock mass behaviour and reliability-based design in the presence of significant geological uncertainty, tasks that currently strain classical computational resources. These capabilities will accelerate the development of digital twins for geotechnical systems, supporting proactive design and operational decision-making.
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