Truck Tray Load Monitoring AI

Measure payload volume and how the load sits in every haul truck tray, at the shovel and before the haul road.

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A dump truck bed filled with rocks, showing digital overlay data for payload, peak height, and load center.

Truck Tray Load AI for the Toughest Open Pits, Quarries, and Haul Fleets

  • Deploy Anywhere, Run Everywhere

    Run truck tray load monitoring on loading face, haul road gantry, and dump cameras on the edge, on-prem, in your VPC, or via API.

  • One Platform, Full Adoption

    Tools every mine operations team can adopt, from production engineers to dispatchers and shovel operators, no separate ML team required.

  • Secure, Compliant, and Audit-Ready

    Data stays safe with SOC 2 Type II compliance, encrypted data, HIPAA compliance, and an uptime SLA.

  • Payload Volume Per Load
  • Off-Center & Front-to-Back Load Distribution
  • Overload & Underload Alerts
  • Tray Load Profile & Peak Height
  • Carryback After Dumping
  • Spill Risk Before the Haul Road
“Achieving positive results using AI in a lab environment is easy, but the real challenge comes when scaling the solution across a network like ours without disrupting day-to-day operations. Our partnership with Roboflow is allowing us to do just that.”

Asim Ghanchi

AVP of Technology, BNSF

Read the full story

Talk to a Vision AI engineer who's shipped in mining.

Bring us your toughest truck payload problem and we'll map a working solution.

Ask us about:

  • Solution architecture that fits your fleet, payload policy, and dispatch system
  • A live demo on your own loading face or haul road camera footage
  • Deployment options: edge, on-prem, air-gapped, VPC, or on the cameras and network your site already runs
  • ROI modeling against tire and frame wear, fuel burn, spillage cleanup, and tonnage left in the pit

Over 80,000 organizations build with Roboflow.

  • Rivian
  • Pella
  • Chobani
  • USG Corporation
  • BNSF Railway
  • American Woodmark
Start where you are

Vision AI is transforming businesses

Customers across the board are solving complex challenges and driving meaningful impact.

  • Automotive customer

    $10 million

    Saved by automatically detecting defects on the production line

  • Logistics & freight company

    90%

    Less time spent manually tracking shipping inventory

  • Building materials supplier

    60%

    Lower customer return rate with improved product quality

Load Every Tray Right, from the Shovel to the Dump

Add a real-time measurement layer to every haul truck tray with Roboflow Vision AI for truck tray load monitoring. Built for open pits and quarries where an overloaded or off-center tray wears tires, stresses the frame, and burns extra fuel, and an underloaded tray leaves tonnage in the pit.

Payload at the shovel:

  • Estimate payload volume in each tray from the load surface, using depth estimation and the tray's known dimensions, and convert it to tonnes with your material density.
  • Alert the shovel or loader operator when a tray is over or under target, so the next pass can be adjusted before the truck leaves.
  • Track loads against your payload policy, such as Caterpillar's 10/10/20 guideline, by truck, shovel, and shift.

Load distribution in the tray:

  • Find the load center side to side and front to back, and flag trays loaded off-center before the truck takes the first bend or ramp.
  • Map the load profile and peak height so material sits inside the tray and stays off the haul road.
  • Compare load shape across shovels and operators to coach loading technique.

Dump, carryback, and the fleet:

  • Detect carryback left in the tray after dumping, so sticky material is cleaned before it eats into the next payload.
  • Tie every load to the truck and cycle, alongside the loading, dump, and cycle counts from heavy equipment detection.
  • Send payload and distribution data to fleet management, dispatch, and production reporting.

Bring intelligence to every tray today. Stop overloads, off-center loads, and carryback from wearing out trucks and leaving tonnage in the pit.

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Frequently asked questions

What is truck tray load monitoring with Vision AI?

Truck tray load monitoring with Vision AI uses cameras at the loading face, a gantry on the haul road, or the dump, with a trained computer vision model (opens in a new tab) and depth estimation, to estimate payload volume in each haul truck tray, show how the load is distributed, flag overloads and off-center loads, and detect carryback after dumping. It can be used with heavy equipment detection, ore car fill detection, and computer vision in mining.

Why does load distribution in the tray matter?

A truck loaded off-center leans toward the heavier side on ramps and bends, which wears tires faster and adds stress to the suspension and frame. A load piled too far forward or back shifts weight between axles, and material heaped above the tray rim can spill onto the haul road.

Does it work alongside onboard payload systems?

Yes. Onboard payload systems weigh the load through the truck's suspension, and cameras add where the load sits, the shape of the pile, and an image of every tray. Results from both can land in the same load record, and the camera reading is ready before the truck leaves the shovel.

Roboflow serves as the measurement engine, and your production and maintenance teams own the payload targets, alert limits, and loading procedures.

Can it integrate with our fleet management and dispatch systems?

Yes. Roboflow sends payload estimates, load distribution, and images over REST (opens in a new tab) or MQTT, or writes them to a database, so they land in fleet management, dispatch, and production reporting. Alerts can go to the dispatcher or a display at the loading unit the moment a tray is off target.

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