Trailer seal verification has long been a necessary drag on warehouse efficiency, slow, manual, and prone to error. Yet with freight volumes rising and throughput expectations tightening, the old model of stop-and-check is increasingly unsustainable. For high-volume facilities, even minor delays at the dock can ripple across the yard and disrupt wider scheduling windows.
Now, edge-based computer vision is emerging as a faster, more reliable alternative. By automating seal inspections in real time, before the trailer even unloads, logistics operators are turning a static compliance step into a dynamic safeguard for both security and productivity.
From Manual Checks to Embedded Vision
Manual trailer seal checks, where dock staff visually inspect and record seal numbers against shipment manifests, remain a weak link in high-velocity warehouse operations. When inbound volume surges, these checks can slow the line or get deprioritized, increasing the risk of theft, misrouting, or compliance gaps that may only come to light during audits or loss investigations.
A broader shift is now underway toward embedded computer vision systems that automate this process. Mounted at dock doors or entry gates, these AI-powered cameras can capture and analyze high-resolution images in real time, with edge devices processing seal data locally to avoid latency. While direct public documentation of trailer seal-specific pilots is limited, logistics leaders are rapidly scaling adjacent applications that lay the groundwork for such use cases.
DHL, for example, has partnered with technology vendors to trial computer vision for a range of logistics tasks, including parcel identification, safety compliance, and dock utilization heatmaps. These trials feed into DHL’s broader smart yard and AI logistics strategy, where visual AI is used to reduce manual labor and increase process certainty across high-throughput facilities.
Maersk, meanwhile, is advancing its Yard Computer Vision initiative, which uses AI to track trailer and container movements throughout yard facilities. By automating asset location, timestamping, and visual inspection, the system supports tighter gate-in workflows and reduces turnaround times. While currently focused on movement detection, this foundation could be extended to seal verification in future iterations.
The On-Dock Verification Stack
Camera-Embedded Dock Frames: Fixed-position industrial cameras mounted at dock doors or inspection points capture every inbound seal automatically as the trailer is positioned.
AI-Based Seal ID Recognition: Trained vision models read embossed, printed, or etched seal numbers, even in low light or partial obstruction conditions. They compare results against advance shipment notices (ASNs) or TMS records.
Tamper Pattern Detection: Beyond reading numbers, the AI flags signs of forced entry, replaced seals, or physical damage, using a library of historical tamper profiles.
Edge Processing Units: Localized analytics hardware processes the feed at the dock, delivering instant pass/fail results without needing a constant high-bandwidth cloud connection.
Integrated Alerting & Workflow Hooks: Failures trigger workflows in the WMS or yard management system (YMS), prompting secondary inspection, photographic evidence capture, and chain-of-custody updates.
What Comes After the Seal?
With embedded vision now a standard safeguard at the dock, the next step is not merely confirming a trailer arrived sealed, but tracing the chain of events on either side of that moment. Linking seal status to real-time trailer telemetry, route deviation alerts, and driver behavior analytics will create a fuller picture of load integrity from origin to unloading. In this model, seal verification becomes not just a checkpoint, but an input into dynamic risk scoring, where every load carries a traceable, data-rich integrity profile that adapts to context, route history, and handling conditions.