ConductVision Enterprise
ConductVision counts forklifts, pallets, trucks and people across docks, yards and aisles, giving warehouse and transport teams loading counts and waiting times by door and hour.
5 detectionsConductVision detections on this photo. Photo: TLSuda, CC BY-SA 4.0, cropped.
Logistics networks operate under relentless pressure to move goods faster with fewer errors, yet warehouse and distribution center visibility remains surprisingly limited. Manual dock checks, barcode-dependent tracking, and reactive damage reporting create bottlenecks that compound across the supply chain. ConductVision's technology can layer computer vision onto existing facility cameras to provide continuous, barcode-independent tracking of containers, pallets, and personnel. Operators can gain real-time throughput dashboards, automated damage detection, and spatial analytics that reveal inefficiencies invisible to traditional WMS data.
Outcomes
Loaders tally pallets by hand as a trailer fills, and the tally can disagree with the shipping order.
Short or over shipments surface only when the customer counts the delivery.
Trucks queue at the gate or in the yard while some dock doors stand empty.
Drivers wait, detention charges build, and the dock loses hours it had free.
Fleet size and rental decisions rest on a manager's sense of how busy the forklifts are.
Sites rent extra forklifts for peaks they cannot measure, or run short at the dock.
Pallets get dropped in aisles and cross-aisles to clear a dock fast.
Blocked aisles slow every pick route and push forklifts into walkways.
Distribution centers lose hours daily to manual dock audits, mis-staged shipments, and damage discovered only at delivery. Forklift traffic conflicts and pedestrian near-misses in high-velocity environments remain difficult to quantify, making safety improvements reactive rather than systematic.
ConductVision can provide continuous visual monitoring of dock doors, staging lanes, and aisle traffic. Container and pallet movement can be tracked without barcode dependency, forklift-pedestrian proximity alerts can reduce near-miss events, and package damage can be flagged at the point of origin rather than the point of complaint.
What the model sees
ConductVision detections on this photo. Photo: Axisadman, CC BY-SA 3.0, cropped.
ConductVision detections on this photo. Photo: GeorgeHillTimber, CC BY-SA 4.0, cropped.
Endpoints
Each endpoint is defined before the pilot starts, with what is counted, its unit and how the results are broken down.
| Endpoint | How it is counted | Unit | Broken down by |
|---|---|---|---|
| PrimaryPallet count match | Share of loaded trailers whose ConductVision pallet count equals the count on the shipping order. | Unit:% | By:Dock door, shift |
| SecondaryYard wait time | Minutes from a truck joining the yard queue to it reaching a dock door. | Unit:minutes (median) | By:Hour, weekday |
| Idle doors with a queue | Minutes a dock door stands empty while at least one truck waits in the yard queue. | Unit:minutes per day | By:Door |
| Forklift moving time | Share of forklift sightings in sampled frames in which the forklift is moving. | Unit:% | By:Area, shift |
| Blocked-aisle minutes | Minutes a pallet stays in an aisle zone past the limit for that aisle, summed per day. | Unit:minutes per day | By:Aisle |
Each pilot measures ConductVision on your own footage against a sample checked by hand, before anyone relies on its numbers.
Pallet count agreement
Difference between the ConductVision pallet count and a reviewer's count from the same loading clips.
pallets per trailer (mean absolute difference) · by dock door
Forklift precision
Share of forklift boxes a reviewer confirms in a hand-checked sample of frames.
% · by camera
Missed pallets
Share of pallets a reviewer marks in sampled frames that ConductVision did not box.
% · by camera, wrapped or bare load
Capabilities
Classifies, counts and tracks cars, trucks, buses, motorcycles and bicycles.
Counts and tracks people in each camera view, by zone and hour.
Reads container codes, wagon numbers, labels and signs from camera frames.
Tracks posture, waiting and movement from pose keypoints in public spaces.
Use cases
Overhead cameras can identify and track containers and pallets as they move between zones without relying on barcode scans. This can close visibility gaps where items are between scan points and flag mis-staged shipments in real time.
Vision models can monitor trailer arrival, door assignment, loading progress, and departure timestamps. Dwell time analytics can identify bottlenecks and enable dispatchers to optimize door allocation dynamically.
Cameras at conveyor transitions and loading zones can detect crushed corners, torn packaging, and deformed boxes. Flagged items can be diverted before shipment, and damage origin points logged for root-cause analysis.
Proximity detection can identify forklift-pedestrian near-miss events and intersection conflicts in real time. Historical heatmaps can reveal chronic danger zones, informing layout changes and traffic pattern redesigns.
Cameras can verify that pallets are placed in assigned zones, detect overflow conditions, and confirm pick-face replenishment. Discrepancies can trigger alerts to warehouse management systems before they cascade into order errors.
Related
Watches stations, robots and crews across the factory floor.
Counts shoppers, queues and carts from the store's existing cameras.
Tracks containers, cranes, trucks and vessels across the terminal.
Pilot
Tell us about your sites and cameras, and a ConductVision engineer replies with a scoping plan built around the endpoints above.
