Reducing Lost Containers in Yards – The Role of Computer Vision

Modern container ports handle immense volumes of cargo, moving millions of containers through their yards each year. Amid this scale, even a tiny fraction of misplaced containers can cause significant operational losses. A lost container in the yard, typically one put in the wrong slot or recorded incorrectly, can cause shipping delays, extra labor, and economic losses.

In this blog, we explore how computer vision technologies, especially AI-powered cameras mounted on container handling equipment like Kalmars, are reducing container misplacement in port yards.

The Hidden Cost of Misplaced Containers in Port Yards

In the fast-paced port yard, misplaced containers are more common than one might think. If inventory accuracy even slips by a tenth of a percent, the impact is huge at scale.

For instance, the world’s busiest port, Shanghai, handled about 47.3 million TEU in 2022, if just 0.1% of those containers were lost or mis-placed, that would mean over 47,000 containers missing in a year. Each misplaced container is not just a needle in a haystack, it’s like a domino that can disrupt operations.

When a container isn’t where the manual system thinks it is, cranes and trucks are forced to wait, reducing productivity. In worst cases, a vessel may have to depart without loading a container that can’t be located in time, a costly failure in customer service.

Misplaced containers trigger a snowball effect in the yard. It often starts with a simple logging error: a driver might place a container in the wrong slot and hit OK on the terminal operating system, unaware of the mistake. The TOS now has incorrect location data. When another container is later assigned to that same slot (unaware it’s already occupied), the driver finds it blocked and must improvise, perhaps putting the container in an alternate spot.

If they don’t report this deviation, one misplaced container leads to others, as each subsequent move happens into further exceptions. Over time, such floating containers, present in the yard but not where they’re supposed to be, accumulate, decreasing yard inventory accuracy.

Challenges of Traditional Yard Management

Why do containers get misplaced in the first place? Traditional yard management face several challenges that open the door to human error and chaos:

• Manual Record-Keeping : In many yards, especially historically, container locations were logged by pen and paper or later via handheld devices. This is slow and prone to mistakes. Writing down or manually keying in container numbers can lead to transcription errors and illegible notes. Manual processes have high error rates, and misidentified or missed entries can lead to misplaced containers and billing errors.
• Complex Yard Operations : A busy terminal is a maze of thousands of containers stacked high, with dozens of handling machines working under tight time windows. Under such pressure, even well-trained drivers can make mistakes. If guidance systems are outdated or reliant on memory and paperwork, the entire placement decision rests on the driver. They might inadvertently put the right container in the wrong place or the wrong container in the right place when rushed.
• Communication Gaps : Yard teams include crane operators, equipment drivers, and ground staff, sometimes from multiple companies. Miscommunication or lack of real-time updates can result in containers being taken to a different block than intended. If one move isn’t immediately reflected in the TOS, subsequent moves might conflict. Containers can effectively vanish from the system’s view due to these unlogged shuffles.
• Outdated Tracking Technology : Many ports still lack precise real-time positioning for yard equipment and containers. Without GPS or RFID-based tracking, the TOS relies solely on driver inputs for container positions. If a driver hits the confirm key at the wrong location, the system is none the wiser.

In summary, traditional yard management is a juggling act of people and machines with limited technology support.

Consequences of a Misplaced Container

When a container goes missing in the yard, the consequences reverberate through port operations and beyond:

• Delayed Ship Operations : If a container scheduled for loading can’t be found in the yard, the loading sequence is disrupted. In a worst-case scenario, if the container isn’t found in a reasonable time, the ship may depart without it. That container then has to catch a later vessel, delaying its cargo delivery by days or weeks.
• Yard Rehandles : A single misplacement often forces additional unplanned moves. Suppose container A was wrongly left in slot X. When another container B is supposed to go to X, the driver finds A already there. Now the driver must find a temporary home for B. Perhaps B goes to slot Y. But slot Y was meant for container C, and so on. This means multiple containers end up in wrong locations. Each extra rehandle not only wastes fuel and time but increases risk of equipment wear-and-tear or accidents.
• Truck and Rail Disruptions : Ports are tightly integrated with truck schedules and sometimes rail timetables. If an import container cannot be located when a trucker arrives for pickup, that truck may have to wait hours or leave empty. Likewise, a container intended for an outgoing train might miss its slot, affecting inland logistics.
• Labor and Resource Drain : When a box is lost, the terminal launches an intensive search operation. This could involve yard supervisors, equipment operators, and even security teams combing through stacks. As one solution provider described, without automated tracking, locating a container among tens of thousands can take days, whereas knowing its last known position turns a search into a simple pickup.
• Security and Safety Risks : Initially, a misplaced container is an operational problem, but it can escalate to a security concern. If a container truly cannot be found, terminals must consider theft or smuggling possibilities. They will notify authorities, check if the box left the premises, or if its contents pose a risk.

Computer Vision – A Game-Changer for Yard Operations

Artificial intelligence (AI) and computer vision technologies are addressing the very root causes of container misplacement. By leveraging cameras, sensors, and smart algorithms, modern ports can automatically track container movements with minimal human input.

One breakthrough is mounting AI-powered cameras directly on container handling equipment, for example, on the spreaders of reach stackers, RTG cranes, or straddle carriers (including popular brands like Kalmar). These rugged cameras watch each container as it is lifted, moved, and stacked, enabling real-time identification and location tracking.

A prime example is Kalmar’s recently introduced smart system. Cameras on the spreader scan the container’s external markings to read its unique ID number, and the system automatically relays this to the Terminal Operating System. The moment a driver picks up a container, the AI vision cameras confirm which container it is and, thanks to integration with yard geo-positioning systems, logs exactly where it’s being placed. This achieves two things: it eliminates manual data entry and it provides continuous, up-to-date inventory records in the TOS.

OCR – Reading Container Codes with Precision

At the heart of these vision systems is Optical Character Recognition (OCR), which enables computers to read the alphanumeric codes on each container. Every shipping container has a unique identification code (four letters followed by seven numbers, e.g. ABCD1234567). Reading these correctly is vital to tracking containers.

Traditionally, a human clerk or driver might jot down or manually key in this code at various checkpoints, a process that tends to make mistakes. OCR technology automates this by using image analysis to instantly recognize the container code, even if it’s in tricky orientations or conditions.

Modern container OCR is remarkably accurate and fast. For example, solutions provided by firms like WebOccult achieve ISO container code recognition rates exceeding 99%. These systems are trained on thousands of container images, learning to handle different fonts, orientations, varying lighting, and even partially damaged numbers. The result is that, in real operational settings, manual container identification errors that could be as high as 20–30% have dropped to less than 1% with automated OCR.

AI-Powered Stacking and Yard Optimization

Beyond just tracking containers, AI is also tackling how and where containers should be stacked in the first place. One reason containers get lost or require extra moves is suboptimal stacking, for example, an import container that a truck will pick up tomorrow ends up buried under five others that won’t move for a week. AI can help prevent such situations through intelligent yard planning and predictive stacking.

Imagine a system that knows, or can reliably predict, when each container in the yard will likely be picked up or needed. AI makes this possible by analyzing patterns and data such as trucking schedules, vessel ETAs, customs clearance statuses, and historical trends. Using this information, the AI can forecast which containers will be needed soon and ensure they are placed in more accessible positions.

The benefits of AI-powered stacking are significant:

• Reduced Re-handling: By minimizing the need to dig out containers, the number of unproductive moves drops. Fewer shuffle moves mean fewer opportunities for misplacement and less wear on equipment.
• Faster Retrieval: When a truck arrives for a container, that box can be retrieved immediately if it’s been intelligently placed, rather than spending an hour moving other boxes around to reach it. This improves turnaround time for deliveries.
• Optimized Space Usage: AI can balance the yard layout by anticipating flows, for instance, clustering containers that are leaving via the same mode or destination, and avoiding dead space. Optimized stacking improves yard density without sacrificing findability.
• Lower Risk of Misplacement: Every extra manual move is a chance for error. If AI stacking strategy avoids unnecessary moves, it inherently lowers the cumulative risk of a mistake. Containers end up moving in a more deliberate, planned manner rather than ad hoc shuffling, so each move is tracked and intentional.

Case Studies – Smart Ports Leading the Way

Forward-looking ports around the world have started reaping the benefits of AI and computer vision in their yards. Let’s look at a few real-world examples that highlight the impact:

Jawaharlal Nehru Port (JNPT), India

As India’s busiest container port (~6.35 million TEU in 2022), JNPT is also upgrading its yard management with modern tech. The port has implemented an RFID-based container tracking system and is now moving toward greater automation.

In 2025, JNPT invited bids to develop an automated empty container yard with an Automated Storage and Retrieval System (ASRS) and real-time container location mapping. This planned smart yard will incorporate OCR-based gate automation and a terminal operating system capable of pinpointing every empty container’s position. The goal is to eliminate the prevalent issues of yard inventory mismatch and improve turnaround times for empties. Even before this, JNPT’s use of RFID tags on containers has helped reduce dwell times by giving authorities better visibility into container movements. By investing in these solutions, JNPT aims to enhance efficiency and avoid the kind of chaotic yard scenarios that lead to lost containers.

Mundra Port, India

Mundra, India’s largest private port, provides a striking example of the benefits of AI-enabled operations. By integrating AI across its logistics, from berth scheduling to yard planning, Mundra achieved over 25% improvement in cargo handling efficiency and significantly shorter turnaround times.

One contributor to this is the use of AI-powered control towers and predictive analytics to synchronize every movement. While the headline here is overall speed, a big part of that is smoother yard workflow, containers are where they need to be when they need to be. Mundra’s adoption of AI-driven OCR and automation at gates and yard equipment (including likely collaborations with tech firms for smart camera systems) has reduced human errors and virtually done away with lost container incidents. The port’s performance is now a case study in how smart infrastructure can transform operations in South Asia. Adani Ports (which operates Mundra) reported handling 8.6 million TEU across its ports in 2022–23, with Mundra alone contributing ~6.6 million TEU. Keeping track of such volumes is impossible with manual methods, but Mundra’s success shows it can be done with AI, securely and efficiently.

Building a Smarter, Safer, and More Efficient Yard

Adopting AI-powered computer vision in the container yard isn’t just about technology for technology’s sake, it directly addresses the long-standing pain points of yard management. By reducing lost containers and improving accuracy, ports unlock a cascade of positive effects: quicker ship turnarounds, lower operating costs, safer working conditions, and happier customers. In an industry where margins are thin and schedules tight, these gains are transformative.

Ready to Transform Your Container Yard? AI vision technology can dramatically improve yard management by reducing errors and boosting throughput. To learn how you can implement AI-powered camera systems and OCR in your port or terminal, consider reaching out to experts in the field. WebOccult, a provider of advanced AI vision solutions for smart yards, can help design and deploy a tailored system that brings these benefits to your operation.
By adopting the right technology today, ports can ensure that lost containers become a thing of the past, and that their yard stays efficient, secure, and ready for the future.

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CEO, WebOccult