AI-Driven Face Mapping

The face mapping module converts excavation-face imagery into structured, design-ready geological outputs for real-time mining workflows.

Powered by AI-driven image understanding, it identifies lithology and structures, separates natural joints from excavation-induced fractures, and enables safer, data-driven excavation.

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Key Advantages

Automated extraction of joints, fractures, bedding planes and structural sets with high precision, even in noisy or blasted conditions.
Dual-head “plane + trace” fusion for high-accuracy structural segmentation and interpretation.
DFN-ready outputs including fracture sets, trace maps and orientation statistics for 3D DFN modelling.
In-shift processing (≤ 2 hours per face) with full audit trail, QA/QC and version tracking.
Highly consistent mapping independent of operator skill or field conditions, reducing subjectivity.

Solving Industry Limitations

Manual mapping is slow, subjective and not scalable for modern, high-production operations.
Difficult to distinguish natural joints from blast-induced fractures using traditional methods.
Conventional outputs are 2D-only and not ready for integrated 3D DFN or numerical workflows.
Lack of real-time geological insights weakens the connection between mapping, design and planning.