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Explore smart port examples showcasing how computer vision enhances safety, streamlines cargo handling, improves navigation, and redefines port management.¡
With over 90% of goods transported by sea, ports are essential hubs for global trade. They serve as vital connectors between land and sea. Ports often handle valuable cargo shipments such as raw materials, manufactured goods, and consumer products, making them key to the international supply chain.
Over the years, cutting-edge technologies have changed how we operate and manage ports worldwide. These innovations have made port management faster, safer, and more reliable. Recent innovations at ports often involve artificial intelligence (AI).
In particular, computer vision (CV), a subset of AI, is making huge waves in port operations. Vision AI makes it possible for computer systems to see and understand visual information in real time. By analyzing images and videos, computer vision models like Ultralytics YOLO11 can identify patterns, detect objects, and track movements in real-time. Insights from image analytics enable more efficient and accurate operations, which has lots of potential in port management.
For example, the Port of Rotterdam, which is the largest seaport in Europe, uses computer vision systems to optimize maintenance schedules. Their AI-powered systems use live video monitoring to keep an eye on ships and port equipment, helping port workers predict when maintenance is needed. Regular monitoring keeps equipment running longer and makes port operations smoother and faster.
In this article, we’ll explore various smart port examples that leverage computer vision technology. We’ll also discuss the advantages and disadvantages of using this innovation in ports while considering its future prospects. Let’s get started!
Ports receive massive amounts of goods daily and face challenges such as keeping operations efficient, ensuring worker safety, reducing traffic jams, and dealing with bad weather. Even a one-hour delay can be costly for shipping companies.
For instance, there are costs related to taking too long to unload cargo (demurrage), holding onto containers too long after unloading (detention), storing goods at the port for extra time (storage fees), and arriving late with their ships (late arrival fees). To avoid these costly penalties, shipping companies aim to carefully plan their schedules, travel times, and port activities.
To manage port operations while addressing these challenges, shipping companies and port authorities are increasingly turning to advanced AI-driven automated solutions. With respect to computer vision, vision models can be trained on vast datasets of images and video clips of port operations.
The trained models can be used for tasks like detecting and tracking cargo containers as they are loaded and unloaded. Computer vision can also help reinforce port safety by tracking port employees who move heavy cargo containers.
Now that we’ve understood why AI and computer vision technologies are important and valuable at ports, let’s take a closer look at some smart port examples that showcase how computer vision can be used.
Computer vision models, like Ultralytics YOLO11 and Ultralytics YOLOv8, can track workers and ensure compliance with safety protocols. How does this work? Both YOLO11 and YOLOv8 support various computer vision tasks, such as object detection, which identifies and classifies objects in an image or video, and object tracking, which monitors the movement of these objects over time.
These tasks can be used in various worker safety use cases. A good example is using object detection to detect personal protective equipment (PPE) on port employees, such as helmets and vests.
Similarly, smart port systems that have been integrated with computer vision capabilities like object tracking can also be used to monitor workers' locations and track their movements in real-time to detect hazards and prevent accidents.
By analyzing live video footage, vision models can identify potential dangers, such as falling objects or workers entering hazard-prone areas. The system can even be configured to send instant alerts if a worker accidentally enters a restricted area or approaches heavy machinery too closely.
Computer vision solutions can play a significant role in improving maritime navigation. Maritime systems integrated with computer vision, Automatic Identification System (AIS) transmissions (signals from the ship containing its identity, location, speed, etc.), and other advanced sensors can be used to obtain insights into the ship's whereabouts. Based on these insights, the AI system can map an ideal route for the ship with less congestion and fuel efficiency. These insights also allow the crew to prepare the port for operations such as loading and unloading without any waiting time.
Computer vision techniques like object detection can be used by port authorities to detect and track objects at sea for safe navigation. For example, the Gulf of Maine Research Institute in Portland uses AI-based camera systems for ship navigation and safety. The cameras use computer vision to detect ships, boats, buoys, people, and other marine hazards, even at night or in foggy conditions. By detecting the obstacles in the sea, ship operators can avoid accidents and navigate easily.
Cargo handling is one of the more complex operations in ports due to the involvement of heavy machinery and the risk of falling objects. Studies show that over 63% of port accidents happen during cargo maneuvering and loading or unloading operations. These accidents can be avoided by reducing the need for workers to be near containers or heavy port equipment for tasks like reading labels or inspecting for damages.
Vision systems can help achieve this by recognizing labels on containers, scanning their size, type, weight, seals, and destinations, or detecting any structural damage. An interesting case study of this is the Piraeus Container Terminal (PCT) of Greece. This port uses Vision AI-integrated cameras to check if the seals on the containers are intact. The system captures images of the front of each container while loading or unloading. Then, object detection is used on the images to locate the seals on the containers. If a seal is missing or damaged, an alert is triggered, notifying the port authorities to investigate further.
Security and surveillance tasks at ports require constant attention. The manpower required to monitor an entire port’s landscape and operations is huge. Even the smallest port in the world, Depoe Bay in Oregon, covers six acres. The vast space and closely stacked containers make it practically impossible for humans to monitor it manually around the clock.
Using computer vision, port operations can be monitored at multiple access points, and any unauthorized entries can be spotted instantly. Optical character recognition (OCR) and automatic number plate recognition (ANPR) technology can read the license plates of vehicles entering and exiting the ports to detect any vehicles that are unauthorized. For an extra layer of security, facial recognition systems can also be used to cross-verify the identities of the drivers and passengers inside the vehicles.
For example, the Port of Valencia in Spain is using a computer vision system that comprises autonomous drones, 5G connectivity, and an augmented reality (AR) headset to monitor the security of the port. Autonomous drones are used to patrol the port on a regular basis, and the video feed is analyzed using vision-based systems through the 5G network. Computer vision models look for any intrusions or suspicious activities. When anything out of the ordinary is detected, alerts are generated. Using the AR headset, the security team can even take a look at the alerted area to understand the severity of the incident.
Oil spills pose a significant environmental threat, especially during loading and discharging port operations. Studies indicate that approximately 29% of medium and small-scale oil spills (7 - 700 tons) occur during these activities. While these spills may not be easily visible and appear harmless, their environmental consequences can be severe.
Manually monitoring such spills is particularly challenging in large port areas. To address this issue, advanced water-sensing cameras equipped with computer vision software can provide an effective solution. By analyzing video footage, these systems can detect oil spills in real-time, enabling prompt responses and cleanup efforts.
In fact, the Port of Antwerp, Europe's second largest port, uses computer vision technology to mitigate the impact of oil spills. Remote-controlled drones monitor the surrounding water areas. Equipped with computer vision abilities, these drones can detect oil spills in nearby port areas. This enables port authorities to identify and address concentrated spill areas promptly, thereby improving the water quality along the seashores.
Adopting computer vision in port management brings many advantages and drives various tailored solutions to unique challenges. Here’s a quick look at some of these benefits:
While CV solutions offer numerous pros, their implementation in ports has certain challenges to consider. Here are some limitations to keep in mind:
According to reports, the global smart port market is projected to grow at an impressive compound annual growth rate (CAGR) of 24.16%, reaching $6.1 billion by 2033. This growth highlights the growing use of advanced technologies like AI, computer vision, and the Internet of Things (IoT) in modern port operations. As ports become more efficient and smarter, computer vision will likely play a critical role in automating tasks, improving safety, and increasing operational efficiency.
When combined with technologies like IoT, blockchain, and big data, computer vision is expected to enable advanced and complex AI-powered solutions, such as real-time cargo tracking and predictive maintenance of port equipment. These innovations will streamline port operations and promote sustainability by optimizing energy use and reducing carbon emissions.
By integrating computer vision into port management, we can enhance safety, efficiency, and security. From monitoring worker activities to automating complex tasks like cargo handling and vessel navigation, computer vision applications can offer a wide range of applications and address critical challenges in port management.
The trend toward automation and AI-driven processes shines a light on the potential of Vision AI solutions. By adopting these advanced technologies, ports can position themselves as leaders in the global maritime industry, contributing to economic growth and environmental sustainability.
Join our community and check out our GitHub repository to learn more about AI. Explore other interesting applications of AI in manufacturing and computer vision in healthcare.
