Smart Glass-Based Next-Generation Mining Visualization System Assisted by RTK GNSS for Real-Time Ore Grade control in OpenPit Mining *Angesom Gebretsadik1,2, Yudai Watanabe 3, Hyongdoo Jang 4, Tony Barnard 4 , Christian Taylor 4 , Natsuo Okada 1, Yoko Ohtomo1, Itaru Kitahara 3, and Youhei Kawamura1 1Division of Sustainable Resources Engineering., Graduate School of Engineering., Hokkaido University, Sapporo, Japan, 060-8628, angstg2007@gmail.com , ohtomoy@eng.hokudai.ac.jp , okadan@eng.hokudai.ac.jp , kawamura@eng.hokudai.ac.jp (*Presenting author: angstg2007@gmail.com ) 2Department of Mining Engineering, Aksum University, Aksum-7080 (Tigray), Ethiopia, angstg2007@gmail.com 3Center for Computational Sciences, University of Tsukuba,1-1-1 Tennoudai, Tsukuba, Ibaraki, 305-8577, Japan. kitahara@ccs.tsukuba.ac.jp , watanabe.yudai@image.iit.tsukuba.ac.jp 4 Minarvis Pty Ltd, Ballarat Central VIC 3350, Australia. H.T.; tom@minarvis.com , T.B; tony@minarvis.com , C.T.; christian@minarvis.com ABSTRACT The ability to visualize ore-grade information in real time at the mine face remains a critical gap in the evolving digital landscape of mining operations. Conventional grade-control workflows rely on post-processing and separate decision-making from field data acquisition, which may lead to delayed responses, inefficient resource utilization, and potential safety risks. To address this limitation, this study presents a smart-glass-based mining visualization framework that integrates wearable augmented-reality technology with Real-Time Kinematic Global Navigation Satellite System (RTK GNSS) positioning as a research prototype to establish a baseline for GNSSanchored spatial visualization in open-pit environments. In the proposed system, grade distributions and spatial boundaries derived from geological models are transformed into lightweight polygon representations and visualized through smart glasses that are spatially aligned with the mine bench. A mobile computing integration hub converts raw GNSS measurements into projected spatial coordinates and synchronizes them with augmented-reality rendering. Field evaluation demonstrates stable visualization with low latency suitable for walking-speed inspection and improved cumulative spatial alignment through RTK correction and sensor fusion, with 0.46 m alignment error observed in the augmented-reality framework. The results indicate that integrating RTK-anchored positioning, polygon-based geological abstraction, and wearable augmented-reality visualization provides a technically feasible and operationally meaningful approach to bench-level grade control. This capability enhances situational awareness, shortens the feedback loop between analysis and excavation decisions, and supports grade-control interpretation, enables visual verification of ore-waste boundaries. The current validation establishes the feasibility of the proposed approach within a controlled research prototype environment. Further field deployment is required to evaluate robustness under varying mining conditions, while production-oriented systems extend beyond this baseline through positioning
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