Edge-AI Deployment Spec Sheet for Underground Drills

Edge-AI deployment in underground drills requires overcoming extreme constraints: limited power (typically 12–24 V DC), high vibration, dust ingress (IP67/IP68 rated enclosures), electromagnetic interference from blasting and LHDs, and intermittent or zero-latency network connectivity. Unlike cloud-based AI, edge models must execute sub-100ms inference on quantized neural networks (e.g., TinyML or TensorRT-optimized U-Nets) fused with real-time sensor streams—such as gyroscopic orientation, bit-load torque, acoustic emission spectra, and downhole gamma-ray spectrometry. The spec sheet defines mandatory interfaces (e.g., CAN bus ISO 11783-12 for drill telemetry, RS-485 for spectral sensors) and validates model accuracy against ground-truth core assay data using domain-adapted metrics like Grade-Weighted F1-Score. Crucially, it mandates dual-mode operation: supervised mode (with human-in-the-loop validation) and autonomous mode (with fail-safe rollback triggers based on confidence thresholds and anomaly detection). Deployment lifecycle management—including model versioning, A/B testing on parallel inference engines, and cryptographic signing of OTA updates—is codified to meet ISO/IEC 62443-3-3 security requirements for industrial control systems.