Quarries can automate truck counts with GPS units on each truck or with camera-based AI at fixed points on site. GPS suits a closed, owned fleet and gives route and cycle data; cameras count every vehicle, contractors included, with nothing fitted to the truck and an image behind every count. Many sites end up using cameras as the independent check, sometimes alongside GPS on their own fleet. Quarry truck counting.
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Accurate truck counts underpin revenue reconciliation, production tracking and customer billing at a quarry. When the truck count is wrong, the error flows through to invoicing and stockpile management.
The two main ways to automate truck counts are GPS-based tracking and camera-based AI. Each has strengths and limitations, the right choice depends on the operation, and some sites combine both.
GPS-based truck counting
GPS tracking systems fit each truck with a GPS device that reports its position at regular intervals. By drawing 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 which truck made which trip, how long each cycle took and the route it followed. This data is valuable for fleet management and can connect to 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 constant challenge: devices get lost, switched off or left in the wrong cab. GPS accuracy in quarry environments can also suffer from terrain, tall stockpiles and nearby heavy equipment.
GPS also tells you where a truck went, but not what happened to it. It cannot confirm that a load was placed, how many loader passes the truck received, or whether it left fully loaded.
Camera-based AI truck counting
Camera-based systems use computer vision to detect and count trucks as they pass defined points on the site. Cameras at the entry gate, loading area or weighbridge approach can identify vehicles, count movements and, depending on the setup, classify vehicle types. Many sites already have cameras in useful positions, so the first step is assessing what's there before adding anything. Adding AI to existing cameras.
The key advantage of camera-based counting is that nothing needs to be fitted to 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, whoever's fleet it belongs to. For quarries that deal with several cartage contractors, that removes device management altogether.
Camera systems also provide visual evidence. Each count is saved with a timestamped image or short clip, creating an auditable record that helps resolve disputes and supports compliance paperwork. Combined with quarry load verification, cameras can also confirm what happened during loading.
The limitations relate to conditions and camera positioning. Dust, rain and low light can affect accuracy, although models custom-trained on the site's own footage cope with them far better than older systems. Camera placement needs planning to give clear sightlines, and lenses need periodic cleaning in dusty environments.
GPS and camera comparison
Deployment complexity: GPS needs a device on every vehicle. Cameras need installation at fixed points on the site, or none at all where existing cameras have a usable view. For sites with a consistent owned fleet, GPS deployment is manageable. For sites with many contractors and changing truck numbers, cameras are easier to deploy.
Ongoing costs: GPS systems typically involve per-vehicle subscription fees and hardware replacement. Camera systems have a fixed infrastructure cost with lower ongoing expenses. As truck volume grows, camera costs stay flat while GPS costs scale with the number of vehicles.
Accuracy: Both approaches can be accurate when set up correctly. GPS accuracy depends on signal quality and geofence calibration. Camera accuracy depends on the model, the camera position and site conditions. Both have edge cases: GPS signal bounce in deep pits, cameras in heavy dust or fog.
Data richness: GPS provides location and timing data. Cameras provide visual evidence and can be extended to count loads, identify vehicle types and monitor safety at the same time.
Combined approach
Some quarry operations combine both. GPS on owned fleet vehicles provides cycle time and route data for fleet planning. Camera-based counting at key points provides an independent, visual check on every vehicle, including contractors. The two data sources cross-check each other.
This combined approach suits larger quarries with several loading areas and stockpiles, where tracking dozens of trucks across a big site benefits from both location tracking and visual verification.
Choosing between GPS and cameras
If you run a closed fleet with consistent vehicles and your main goal is fleet planning, GPS may be the right starting point. If you work with several contractors, need visual evidence for billing disputes, or want to extend into vehicle, safety and site monitoring, camera-based AI will usually deliver more value for the cost.
For most quarries with a mix of owned trucks and contractors, camera-based counting is the broader foundation, and the same cameras can take on further monitoring jobs over time. Quarry truck counting.