Canopy Vision Blog

Leveraging A.I. Vision and LiDAR for Railcar Loading and Unloading Operations

LiDAR point cloud showing volumetric fill levels in two railcars during loadout

Most industrial rail loadout stations have a scale that weighs the railcar before and during loading. This allows operators to ensure they are loading the car with as much material as possible without exceeding the car’s maximum Gross Weight on Rail (GWR). Since every car has a slightly different weight when empty (the Tare Weight), each car has a Load Limit that can be added to the car before it reaches its maximum GWR.

This is all straightforward — load your railcars up to the maximum allowed by the rail operator to optimize and maximize your rail efficiency.

When You Don’t Have a Scale at Every Loadout

But what if you don’t have a scale? Scales are an expensive capital project, and depending on your site layout, you might have multiple loadout stations that do not have a scale underneath them, relying instead on a single scale near the exit of the facility to capture the legal-for-trade measurements prior to leaving the facility. At facilities like this, operators might be loading by eye, which can cause cars to be overloaded or not filled to their maximum capacity. Understanding what drives project cost helps teams compare a new scale installation with sensor-based alternatives at each loadout point.

Unloading Without a Scale at Receipt

If you receive cars to unload, you might not have a scale when cars are received and unloaded, causing your operations to instead rely on the values reported by the rail operator or the facility that loaded the cars. Small errors, spills, or other data inaccuracies can cause incorrect reporting of what you are unloading, resulting in inventory write-downs or yield calculation errors. Similar inventory and procedure risks show up in other receiving workflows — for example, teams monitoring truck unloading procedures with AI vision use cameras to add an independent record when manual checks alone are not enough.

Volumetric Measurement With Cameras and LiDAR

Canopy Vision has partnered with Altamus, a leader in industrial LiDAR solutions, to provide a low-cost volumetric railcar measurement solution that combines cameras and LiDAR to measure the volume of material being loaded into a railcar or the volume prior to and after unloading. This system works well even for operations where the car is moved during the loading process, which means operators will have a real-time estimate of loaded quantities rather than waiting for the car to pass under a fixed LiDAR scanner after the car has finished loading.

For yards that also need car identity and movement context at loadout or gate points, volumetric data can complement AEI RFID and camera pass-by tracking and broader automated railcar tracking in the yard. Measurements and video can flow through the Canopy Vision platform alongside other rail and process-monitoring deployments.

Rendering of LiDAR and AI vision for railcar loading and unloading operations.

Volume, Density, and Existing Scales

With LiDAR, the data is volumetric, requiring a material density to convert the volume to weight (tons). For operations with highly variable material densities, this solution may not be ideal. On the other hand, for facilities that already have a scale and would like to gather real-time car-by-car density measurements, this solution can provide that data by combining the volumetric data with the scale output to calculate each car’s density without relying on manual samples or other error-prone autosamplers.

If your facility has loading or unloading operations and would like to understand whether a Canopy Vision / Altamus LiDAR solution can help, please contact sales@canopy-vision.ai or reach out through our contact form. You can also explore related rail solutions and examples in our use case library.

Need better visibility at loadout or unload?

Canopy Vision and Altamus help industrial teams measure railcar fill volumetrically with cameras and LiDAR—including when cars move during loading—so you are not relying on eye estimates or post-load scans alone.