Tire Condition Monitoring AI

Spot cuts, sidewall damage, bulges, and tread wear on every haul truck and loader tire as it rolls past.

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AI system analyzing large mining truck tires, identifying sidewall and tread cuts, and counting wheel nuts.

Tire Condition Monitoring AI for the Toughest Open Pits, Quarries, and Haul Roads

  • Deploy Anywhere, Run Everywhere

    Run tire condition monitoring on go-line, fuel bay, shop, and handheld cameras on the edge, on-prem, in your VPC, or via API.

  • One Platform, Full Adoption

    Tools every maintenance and tire team can adopt, from reliability engineers to tire technicians and shift supervisors, 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.

  • Tread Cuts & Rock Damage
  • Sidewall Cuts, Bulges & Separations
  • Tread Wear & Irregular Wear Trends
  • Missing Wheel Nuts & Rim Damage
  • Tire ID & Position Per Truck
  • Drive-Through Go-Line Inspection
“Roboflow has been instrumental in accelerating our deployment of innovative AI solutions.”

Travis Turnbull

Vice President & CIO, Pella Corporation

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

Bring us your toughest tire condition problem and we'll map a working solution.

Ask us about:

  • Solution architecture that fits your fleet, tire management program, and maintenance system
  • A live demo on your own go-line or walkaround tire images
  • Deployment options: edge, on-prem, air-gapped, VPC, or on the cameras and network your site already runs
  • ROI modeling against early tire removals, tire failures, truck downtime, and lost tonnage

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

Inspect Every Tire, from the Go-Line to the Tire Shop

Add a real-time inspection layer to every haul truck, loader, and dozer tire with Roboflow Vision AI for tire condition monitoring. Built for open pits and quarries where a single ultra-class tire can cost $60,000 to $100,000, and a cut that goes unnoticed for one shift can end a tire's life early.

Damage on every pass:

  • Detect cuts, gouges, and rock damage in the tread as trucks roll through a camera station at the go-line, fuel bay, or shop entrance.
  • Flag sidewall cuts, bulges, and signs of separation, and send the truck to the tire shop before the next haul cycle.
  • Check for missing or loose wheel nuts and visible rim damage on every wheel position.

Wear and tire history:

  • Track visible tread wear and irregular wear patterns by tire and position so the tire team can plan rotations and replacements.
  • Read tire size and serial numbers from the sidewall to tie every image to the right tire.
  • Build an image history for every tire across its life, from install to scrap, for warranty claims and supplier reviews.

Root cause and the haul road:

  • Trend cuts and damage by truck, route, and shift to find the stretch of haul road, loading face, or dump that is costing tires.
  • Catch unusual damage that was never labeled with anomaly detection that learns what a healthy tire looks like.
  • Pair tire monitoring with the rest of computer vision in mining, from fragmentation to haul cycle tracking.

Bring intelligence to every tire today. Stop small cuts from becoming failed tires, idle trucks, and lost tonnage.

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Frequently asked questions

What is tire condition monitoring with Vision AI?

Tire condition monitoring with Vision AI uses fixed cameras at the go-line, fuel bay, or shop entrance, or photos from walkaround inspections, with a trained computer vision model (opens in a new tab) to find cuts, sidewall damage, bulges, wear, and missing wheel nuts on haul truck and loader tires. Each finding is tied to the truck, wheel position, and tire. For inspection in tire manufacturing, see tire defect detection.

Why monitor haul truck tire condition with cameras?

Haul truck tires are among the biggest operating costs in a mine, and cuts from sharp rock and spilled material are a leading cause of early failure. Shift walkarounds catch a lot, and a camera station adds a check of every tire on every pass, done the same way each time, with an image of what it saw.

Does it work with our tire management and tire pressure systems?

Yes. Tire pressure and temperature systems report what is happening inside the tire, and cameras add what the outside looks like: cuts, bulges, wear, and wheel nuts. Results from both can land in the same tire record.

Roboflow serves as the inspection engine, and your tire and maintenance teams own the removal criteria and repair decisions.

Can it integrate with our fleet and maintenance systems?

Yes. Roboflow sends findings, images, and tire IDs over REST (opens in a new tab) or MQTT, or writes them to a database, so they land in tire management, fleet management, and maintenance systems as work orders. Alerts can go to the tire shop and dispatch the moment a truck passes with damage.

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