KalPRO HaulSight by Kal Tire and Decoda: design and safety insights for mine fleets
Reviewed by Tom Sullivan

First reported on MINING.com
30 Second Briefing
Kal Tire’s Mining Tire Group and Australian tech firm Decoda have launched KalPRO HaulSight, using front- and rear-mounted LiDAR and camera sensors plus an on-board edge computer to give real-time alerts on spillage, road undulations and high G‑force events across entire haul circuits. The system integrates with Kal Tire’s TOMS platform, allowing condition monitoring teams to auto-generate priority-based work orders and guide operators into safer loading and dumping positions. Tested for 18 months on Canadian mine sites in sub-zero conditions, HaulSight also quantifies trade-offs between lost tyre life, productivity, fuel burn and haul road upgrade costs.
Technical Brief
- Decoda’s LiDAR–camera package is mounted both front and rear on haul trucks for full-path coverage.
- An on-board ‘edge’ computer processes sensor feeds locally, avoiding latency and connectivity dependence for hazard alerts.
- Integration with Kal Tire’s TOMS lets condition monitoring teams convert flagged hazards into automated, priority-ranked work orders.
- HaulSight’s planning module explicitly compares tyre-life loss, productivity penalties and fuel burn against haul road upgrade costs.
Our Take
With 576 Mining stories and over 1,100 tag-matched pieces in our database, safety-tagged items like KalPRO HaulSight remain a minority compared with production or exploration coverage, signalling that digital safety and tyre-management tools are still a niche but growing focus area.
The 18‑month testing period on Canadian mine sites suggests Kal Tire’s Mining Group is positioning HaulSight as a production-grade operational tool rather than a pilot, which could make it easier for large Australian and Canadian operators to justify integration into existing fleet management and TOMS-style systems.
Linking HaulSight to the earlier KalPRO TireSight project indicates Kal Tire is building a modular data ecosystem around tyres and haulage rather than a single product, which typically improves stickiness with mine operators once embedded across multiple workflows.
Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.
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