Automated Truck Counting for Quarries: GPS vs Camera-Based Solutions
Accurate truck counting at a quarry is not a nice-to-have. It is the foundation of revenue reconciliation, production tracking, and customer billing. When your truck count is wrong, everything downstream — from invoicing to stockpile management — is wrong too.
Two technologies have emerged as the leading approaches to automating truck counts: GPS-based tracking and camera-based AI. Both have their strengths. Both have their limitations. The right choice depends on your specific operation, and in some cases the best answer is a combination of both.
GPS-Based Truck Counting
GPS tracking systems work by fitting each truck with a GPS device that reports its position at regular intervals. By defining geofences around key locations — the loading area, the weighbridge, the stockpile, the exit — the system can count how many times each truck enters and leaves each zone.
The main advantage of GPS is that it tracks individual vehicles. You know exactly which truck made which trip, how long each cycle took, and the route it followed. This data is valuable for fleet management and can integrate with dispatch systems.
The limitations are practical. Every truck that enters your site needs a GPS unit, which means either fitting your own fleet or requiring contractors to carry compatible devices. Contractor compliance is a persistent challenge — devices get lost, turned off, or left in the cab of the wrong truck. GPS accuracy in quarry environments can also be affected by terrain, tall stockpiles, and the proximity of heavy equipment.
GPS also tells you where a truck went, but not what happened to it. It cannot verify that a load was actually deposited, how many scoops it received, or whether the truck was fully loaded.
Camera-Based AI Truck Counting
Camera-based systems use computer vision to detect and count trucks as they pass through defined points on the site. Cameras positioned at the entry gate, loading area, or weighbridge approach can identify vehicles, count movements, and — depending on the system — classify vehicle types.
The key advantage of camera-based counting is that it requires nothing on the truck. There is no device to install, no contractor compliance to manage, and no per-vehicle cost. Every truck that passes the camera is counted, regardless of whose fleet it belongs to. For quarries that deal with multiple cartage contractors, this is a significant operational simplification.
Camera systems also provide visual evidence. Each count is associated with a timestamped image or video clip, creating an auditable record that is useful for dispute resolution and compliance documentation. When combined with AI scoop counting at the loading point, camera systems can verify not just that a truck was present but exactly what happened during loading.
The limitations of camera-based systems relate to environmental conditions and camera positioning. Dust, rain, and low light can affect accuracy, though modern AI models handle these conditions far better than earlier systems. Camera placement needs to be carefully planned to ensure clear sightlines, and cameras need periodic cleaning in dusty environments.
Head-to-Head Comparison
Deployment complexity: GPS requires a device on every vehicle. Cameras require installation at fixed points on the site. For sites with a consistent owned fleet, GPS deployment is manageable. For sites with many contractors and variable truck numbers, cameras are simpler.
Ongoing costs: GPS systems typically involve per-vehicle subscription fees and hardware replacement costs. Camera systems have a fixed infrastructure cost with lower ongoing expenses. As your truck volume increases, camera costs stay flat while GPS costs scale with fleet size.
Accuracy: Both approaches can achieve high accuracy when properly deployed. GPS accuracy depends on signal quality and geofence calibration. Camera accuracy depends on model quality, camera positioning, and environmental conditions. Both can be affected by edge cases — GPS by signal bounce in deep pits, cameras by heavy dust or fog.
Data richness: GPS provides location and timing data. Cameras provide visual evidence and can be extended to count scoops, detect vehicle types, and monitor safety compliance simultaneously.
The Combined Approach
Some quarry operations are finding the most value in combining both approaches. GPS on owned fleet vehicles provides cycle time and route data for fleet optimisation. Camera-based counting at key points provides the independent, visual verification layer for all vehicles including contractors. The two data sources cross-validate each other, creating a high-confidence count.
This combined approach is particularly valuable for larger quarries running multiple loading areas and stockpiles, where the complexity of tracking dozens of trucks across a large site benefits from both location tracking and visual verification.
Which Should You Choose?
If you operate a closed fleet with consistent vehicles and your primary goal is fleet optimisation, GPS may be the right starting point. If you work with multiple contractors, need visual evidence for billing disputes, or want to extend into safety monitoring and production tracking, camera-based AI will likely deliver more value per dollar invested.
For most Australian quarries dealing with a mix of owned trucks and contractors, camera-based counting provides the broader foundation — one that can be extended over time as the operation identifies new use cases for the same camera infrastructure.
Get an accurate count
We will assess your site, review your current counting process, and recommend the approach that fits your operation — GPS, camera-based AI, or a combination of both.