Securing Shipping Lanes Through the Use of Artificial Intelligence (AI)

Artificial Intelligence, or AI, continues to take the world by storm. However, its impact isn’t limited to just conversations through chatbots and virtual assistants. It is rather being used in various industries to reduce cost and chances of human error as well as improve efficiency, bring more sustainability, and introduce better safety precautions.

Maritime is one such industry where AI is showing immense potential and revolutionizing the way it operates, which holds great significance due to the maritime industry being responsible for the transportation of more than 90% of the world’s commerce.

Given the maritime sector’s importance in global commerce and companies trying to stay competitive, utilizing machine learning algorithms in shipping operations is crucial. With the global economy being a complex and challenging environment, even minor improvements can bring in substantial benefits.

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The Scope of AI in the Shipping Industry

As we know, shipping lanes hold immense importance in the global economy for being economical and environment-friendly. This calls for the need to have safe and efficient means of transportation to move goods across countries all over the world. Hence, it becomes vital to use AI to secure these lanes.

In this context, advanced technologies are leveraged to collect, analyze, monitor, and respond to various challenges shipping lines face. For instance, AI-powered systems provide real-time data for ship routes and enhance navigation while constant surveillance through sensors prevents security threats. Moreover, AI algorithms analyze data to predict maintenance needs, hence reducing downtime and ensuring ships are operating at peak performance.

As NauticExpo estimated a few years ago, the revenue of global maritime freight transportation can surpass $200 bln by 2023, but for that to happen, the industry “will need to add AI to its armory of digital technologies.”

In the shipping industry, AI can help shipping companies automate tasks, improve planning, optimize operations, make better decisions, and increase safety. It further helps in distribution planning, streamlining loading and unloading operations, intelligent scheduling, and adjusting to the changing market realities and market demand. In addition, the use of AI can be of great help in navigation controls, securing communication systems, and improving emergency response, contributing to overall shipping safety.

A survey by Navis found that a large number of participants agree that AI could be involved in automating processes, most importantly for container handling equipment assignments and decking systems. Other participants also see AI’s usage in recommended actions and predicting gate volumes as well as stowage of vessels. However, lack of technology and expertise is the biggest challenge with AI, which is understandable given that the technology is still new.

To help with this, companies have already started taking steps. For instance, the Orient Overseas Container Line (OOCL) collaborated with Microsoft’s Asia-based research arm to improve shipping network operations through AI. As part of the partnership, the idea has been to train AI developers through machine learning and intensive training sessions.

Making Use of Data for Security

It is important to note that effective AI is dependent on data — everything from learning to prediction AI needs diverse and massive data sets for it to perform well. So, as the shipping industry gets better at working with complex and big data sets, it can build new AI systems to help humans operate vessels in a much more efficient and safe manner.

Most recently, scientists at the University of Victoria and the University of Copenhagen’s Niels Bohr Institute used AI to predict the occurrence of large rogue waves that damage not just ships but also oil rigs. Researchers made use of enormous amounts of big data, 700 years’ worth, about ocean movements to discover a mathematical model that can predict the likelihood of such waves.

“In the study, we mapped the causal variables that create rogue waves and used artificial intelligence to gather them in a model,” said Dion Häfner, a former Ph.D. student at the Niels Bohr Institute and author of the scientific study, “which can calculate the probability of rogue wave formation.”

For this, the data was collected from buoys in over 150 different locations around US coasts as well as overseas territories 24 hours a day. The study recorded 100,000 waves as rogue waves. By using machine learning, the researchers turned it all into an algorithm. The study found that this rogue wave happens due to the factor known as “linear superposition,” something that has been around for 300 years but is now supported with data.

What it means for the shipping industry is that cargo ship companies can use this algorithm to predict when the risk of such a dangerous wave occurs and then plan their routes in advance.

Additionally, organizations like Singapore Management University (SMU), Fujitsu, and A*STAR’s Institute of High-Performance Computing (IHPC) have also been working for some time on developing big data and AI technologies for vessel traffic management in Singapore’s port as well as the world’s busiest sea lanes, the Straits of Singapore and Malacca.

These organizations have been developing technologies that use real-world data to improve congestion forecasting and identify any potential collisions. The idea has been to have next-generation maritime traffic coordination technology, much like air traffic control.

With this advance of autonomous ships, according to Professor Lau Hoong Chuin, SMU’s Lab Director and Lead Investigator of the Urban Computing and Engineering Centre of Excellence (UCE CoE):

“The technology can potentially disrupt vessel traffic management to reduce human errors and improve navigational safety.”

Meanwhile, Singapore’s Tuas Port aims to be the world’s largest fully automated port by 2040 by making use of the Next Generation Vessel Traffic Management System (NGVTMS) developed by Singapore’s Maritime Port Authority.

Automating the Shipping Industry

It’s been over a decade that machine learning and AI have been shaping the maritime landscape, and it keeps on growing. One of the areas where the development has been happening is unmanned navigation for certain tasks, such as autonomous ships crossing busy shipping lanes safely or navigating through complex transportation channels.

According to a 2023 joint report by Lloyd’s Register and Thetius, a maritime innovation consultancy, the vessel autonomy markets and AI-driven systems will be worth a combined $5 bln in five years.

With ships growing in number and size, there has been a rise in potential collisions. According to the European Maritime Safety Agency, 4000 collisions and incidents were reported annually between 2014 and 2019, with a vast majority of them (up to 96%) attributed to human error.

As a result, autonomous and remote-controlled ships are being trialed with sensors through the help of radar, LIDAR (Light Detection and Ranging), sonar, GPS, and AIS providing data to help in navigation.

Back in 2018, Sea Machines Robotics and Denmark-based A.P. Moller-Maersk worked together to test an AI-powered system on a container ship, which was the first time the maritime industry saw the installation of computer vision along with LiDAR and perception software aboard to improve and upgrade transit operations.

For this, Sea Machines adopted an AI-based solution, which is similar to data-driven assistance systems found in cars, to improve situational awareness at sea along with identification and tracking of objects. The solution uses advanced sensors to gather a continuous stream of information from a vessel’s environmental surroundings, which is used to identify and track potential conflicts and then displayed efficiently to facilitate safer and more efficient maritime operations.

The automation of the shipping industry is gaining significant traction. Japanese shipping firm Mitsui OSK Lines (MOL) and Chinese tech company SenseTime, known for their collaboration with Honda on self-driving cars, are now conducting research to leverage AI in ship image recognition systems.

Under this, SenseTime’s system uses ultra-high-resolution cameras and a GPU to automatically identify vessels in the surrounding area in order to help stop large vessels colliding with smaller ones and improve safety.

This image recognition technology, which is developed by combining AI deep-learning tech with MOL’s extensive maritime experience, can also be used to monitor shipping lanes.

Recently, in November, Michigan Central, the mobility innovation arm of Ford and tech hub Newlab, launched a pilot project to automate the shipping industry. During this eight-week project, the partners tested a self-driving vessel from Mythos AI that digitally maps the underwater landscape in Detroit’s Port of Monroe and the surrounding Great Lakes waterway.

By creating a digital twin of the area, the vessel aims to provide cargo ships with greater insights to improve their processes. The data collected will be used to create fully autonomous shipping routes, train autonomous vessels in the future, and roll out autonomous, low-emission boats. Mythos AI CEO Geoff Douglass:

“Self-driving vessel technology will reshape maritime logistics. Scaling this innovation to other ports will transform antiquated systems, reduce emissions, and drive economic growth on a global scale.”

Companies Leveraging AI for Securing Shipping Lanes

A 2019 McKinsey Global AI Survey found a nearly 25% year-over-year (YoY) increase in the use of AI in standard business processes across multiple areas of business. Logistics, in particular, is an AI-driven industry thanks to technology’s great potential to improve the maritime industry by eliminating regular tasks.

But this is not all. McKinsey’s separate cross-industry study on AI adoption found that early adopters with a proactive strategy in the logistics sector enjoyed more than 5% profit margins.

AI can clearly deliver considerable benefits to shipping operations, and those who actually take action and start incorporating AI into their business can build more efficient networks, have an advantage over the competition, and be best prepared for the future.

Today, there are several companies that are exploring and implementing AI for safe shipping lanes.

1. Rolls Royce

Rolls-Royce is one such company that has been working on autonomous shipping and using AI to enhance navigation and safety in maritime operations. Over the past many years, the company has unveiled several solutions to mitigate safety risks, including the Intelligent Awareness (IA) system and fully autonomous commercial vessels. For its efforts, Rolls-Royce has partnered with Intel and Google.

In 2022, Rolls-Royce experienced a notable financial upturn, with its revenue climbing to £12.691 billion, a substantial increase from the previous year’s £10.947 billion. The company also reported a significant rise in underlying operating profit, reaching £652 million, marking an improvement of £238 million compared to the prior year.

2. Wärtsilä

Technology company Wärtsilä is another one involved in developing smart shipping technologies, including the use of AI for navigation and safety. The company has been building intelligent port solutions, ship-to-shore secure data communications, and interoperability in e-navigation.

The company reported a 6% increase in order intake, reaching EUR 6,074 million, up from EUR 5,735 million in the previous year. It also saw a significant 22% rise in net sales, totaling EUR 5,842 million, compared to EUR 4,778 million in 2021, with 48% of these sales attributed to services.

3. Nippon Yusen Kabushiki Kaisha

Nippon Yusen Kabushiki Kaisha (NYK), a major Japanese shipping company, demonstrated its collision avoidance system back in 2021. Orca AI, which uses vision sensors and thermal cameras besides AI-powered algorithms, is engineered for vessels to have a new lookout support system that provides them with enhanced visibility, especially in difficult conditions, hence preventing human error.

In FY 2022, Nippon Yusen Kabushiki Kaisha (NYK) had substantial liquidity with cash and deposits of approximately $1.9 billion. It also reported a considerable sum of receivables, including trade and contract assets, at nearly $2.9 billion, with its inventory assets standing at around $466 million.

Notable Players

A.P. Moller-Maersk, one of the largest shipping companies globally, has been actively using digital technologies and AI to optimize shipping operations and improve safety.

Meanwhile, Sea Machines Robotics is a Boston-based company that develops autonomous vessel control systems that incorporate AI for increased safety and efficiency in maritime operations. The company is credited with pioneering the first industrial-grade control system designed to enable autonomous and remote operation of commercial marine vessels, including workboats. It is also developing advanced perception technology for different types of vessels along with navigation assistance tech.

Then, there is Shipping giant MSC, which boasts of launching the ID-based container pick-up, a first for the industry. Instead of using a PIN code to release containers and transport them, the tech basically makes use of ID and biometric data, thus making the process more efficient and secure.

Norway-based Kongsberg Gruppen has also been involved in developing autonomous and AI-driven solutions for the industry, with other participants being Bedrock Ocean Exploration, Ladar, Soshianest, i4 Insight, Buffalo Automation, Arinto Maritime GmbH, Vake, and Massterly.

Conclusion

As we saw, AI has been seeing vast implementation and benefits in the shipping industry in terms of predictive scheduling and maintenance, autonomous ships, route forecasting, organizing container positioning, optimizing fuel consumption, emissions reduction, streamlining back office operations, demand predictions, and dynamic pricing.

Of course, AI is not without its issues, with key obstacles in its widespread adoption being shortage of specific skills, poor quality of data, lack of a clear strategy, and trust issues. Not to mention, a vast majority of large vessels don’t really have the right communication capacity. Then, there are regulatory barriers to AI’s wide adoption.

Despite all this, the potential of AI is simply hard to ignore, with its implementation seeing growing support. Over time, as technology advances and the use of AI grows in the sector, we are bound to see a great transformation in the shipping industry.

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