Why the technology choice matters
Collision prevention is only as good as its ability to reliably sense a hazard in your environment — and mining environments are hostile to sensing. A technology that works flawlessly on a clean surface haul road can misbehave in a dusty, curving underground heading full of reflective steel. Picking the wrong sensing approach is how projects end up with false alarms operators learn to ignore, or missed detections that defeat the whole point. So before comparing vendors, it's worth understanding what each underlying technology can and can't do.
First principle: detection technology is necessary but not sufficient. Under MHSA 8.10.1 the system must detect, warn and intervene (EMESRT Level 9) — see our collision-prevention compliance guide. Judge the whole system, not a single clever sensor.
The main technologies
- RFID / RF tags. Each person and vehicle carries a tag; readers detect tagged entities reliably and identify who/what they are. Strength: robust identification, works in dust and dark. Limit: it only sees tagged things — an untagged person or obstacle is invisible — and basic versions give zone presence rather than precise distance.
- Ultra-wideband (UWB). A tag-based RF technology that adds precise, real-time distance measurement. Strength: accurate ranging, performs well underground, good for tight vehicle-pedestrian distances. Limit: still tag-dependent (untagged hazards unseen), needs reader infrastructure.
- Radar. Detects objects whether tagged or not, measuring range and closing speed. Strength: works in dust, smoke and darkness, sees untagged hazards. Limit: coarser at telling a person from a rock or a wall, and reflective surfaces and confined geometry can create clutter.
- LiDAR. Builds a detailed 3D picture of surroundings. Strength: high spatial detail and obstacle mapping. Limit: degraded by heavy dust, water and poor visibility — a real constraint in many workings — and higher cost.
- Camera / AI vision. Classifies what it sees (person vs vehicle vs structure). Strength: rich classification, good on surface in good light. Limit: dust, darkness and glare hit it hard underground; needs good lighting or augmentation.
The technologies on one table
| Technology | Range | Sees through dust/obstacles | Precision | Weakness |
|---|---|---|---|---|
| RF / RFID tags | Tens of metres | Yes | Zone-level | Only detects tagged things; multipath in tunnels |
| UWB | Tens of metres | Yes | Sub-metre with direction | Tag-dependent; anchors and time-sync |
| Radar | Tens to 100+ m | Yes — dust, rain, dark | Good range and velocity | Cannot identify what it sees; clutter |
| LiDAR | Tens of metres | Degraded by heavy dust | High spatial detail | Dust and water spray; cost |
| Camera + AI | Tens of metres | No — needs light and clear air | Identifies people and objects | Dark, dust, glare, mud on the lens |
| GNSS / V2V | Hundreds of metres | Yes (surface only) | Metres | No sky underground; latency |
| Fusion | Per sensor | Best of each | Best of each | Integration and validation effort — the reason it usually wins anyway |
Why fusion usually wins
Because each technology covers another's blind spot, robust systems combine them. A common pattern: RF/UWB tags for reliable identification and precise distance between known people and machines, plus radar (and, on surface, camera/LiDAR) to catch untagged hazards and obstacles. The fusion gives you both "I know exactly where my tagged people are" and "there's something in the path I didn't expect" — which neither alone provides. The right blend depends entirely on whether you're surface or underground, your dust and lighting, your geometry, and your fleet.