What this means in practice

  • A fixed camera at the dock door or return lane counts the stacks of totes, crates or bins on each pallet or cart, and reads any printed code, label or color that shows the type or owner.
  • Each count is matched to the truck, route or customer and the date, so the team can see how many went out, how many came back, and where the gaps are building up.
  • The model is trained on the clients own containers. It can also flag cracked walls, broken handles, missing lids, labels it cannot read, and containers that look dirty and need another wash.
  • A dock lead checks every flag and any count that looks off before a customer is asked for returns or a container is thrown away. The camera points at the stacks, not at people, and any people or plates caught in view are blurred.
  • Start with one dock door and one container type, compare the camera count with the hand count for a few weeks, and keep the existing wash, food safety and paperwork steps in place.

How Lid Vizion approaches it

We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.