“Our cars, our medical devices, our household appliances are all now computers with things attached to them. Your refrigerator is a computer that keeps things cold, and a microwave oven is a computer that makes things hot. And your car is a computer with four wheels and an engine. Computers are no longer just a screen we turn on and look at, and that’s the big change.” Bruce Schneier, MIT Technology Review Interview
“Software is eating the world, and A.I. is eating software”. Amir Hussain
As recently as last year, digitisation in the shipping industry was viewed with apprehension. For example, in our article “6 Maritime Startups that are Changing the Game” Vesselbot CEO Constantine Komodromos described shipping industry reactions to an e-auction platform for freight: "A large number of market participants coming from various seniority levels was stating that digitization is just a topic to be discussed at conferences, and not something that could be potentially reforming the market.” Fast forward to the present and the active adoption of disruptive technology has now become a reality with cargo shipping companies such as Kongsberg, Rolls Royce, OOCL, CMA-CGM, Maersk, MOL, DNV GL and Wärtsilä, Ferry Operator Stena Line and Cruise Line Carnival all incorporating digital technologies such as machine learning and AI.
Whether shipping organizations work together with huge companies such as Microsoft and Google or one of the many new maritime startups (whose numbers have recently exploded with “more than $3.3 billion …invested in digital startups in the shipping and logistics sector”) it appears that shipping is not just ripe for change anymore, it’s changing. If you need more convincing, a recent Inmarsat survey of 125 global ship owners found that “ship owners are far more open to deploying IoT tools for analytic, management, and operational purposes than some other industries, including mining and agriculture” and “average expenditure per business on IoT based solutions will amount to $2.5 million over the next three years” while IDC tells us that “The DX (digital transformation) programs that will receive the most funding in 2018 are digital supply chain and logistics automation ($93 billion)”. An industry that has often been described as “behind the times” is now proving itself to be quite the opposite. With this in mind, I ask several experts in shipping and maritime innovation and technology, representing both large organizations and startups, to share their thoughts on how they see AI impacting the shipping industry right now.
Wolfgang Lehmacher, Head of Supply Chain and Transport Industries, World Economic Forum @W_Lehmacher
At times, 8% of the world bulk carrier fleet has been stuck at anchorage. With bigger ships resulting in lower frequency services and greater volume peaks the situation will not improve. Port congestion is part of the flow and volume forecasting and management challenge. Artificial intelligence, in conjunction with internet of things and big data, can improve visibility and predictability. Recently, the Port of Rotterdam and the Port of Hamburg have started to share port call data to optimize calls of liners. The solution is not solely technical though: shipping contracts and berthing priority policies need also to be adjusted.
Mike Konstantinidis, CEO, METIS @MKonstantinidis
The biggest problem for the shipping industry that AI can solve is the most obvious one: maximizing profits. In maritime it is all about using minimum resources for ensuring maximum efficiency of engines, optimizing routes, improving cost-effective operation of equipment onboard and of course, minimizing fuel consumption. Our company’s product METIS is a cyber “personal assistant” for vessel monitoring and management which is powered by AI (Artificial Intelligence). METIS interacts with all executives at a shipping company via Natural Language Processing, dramatically decreasing the time required for daily decision making, regarding vessel performance analysis, engine and cargo monitoring, operation safety and regulatory compliance. The software detects noteworthy events, makes complex prognostics and diagnostics, prepares reports, proposes corrections and calculates KPIs to achieve the desired optimum performance.
Thomas Bruun Clausen, Business Development Manager, Alfa Laval @ThomasBClausen
Seen from a supplier’s point of view AI will be able to empower shipping to turn ever increasing complexity from a challenge to an opportunity. It will allow us to scan that complexity faster, getting to asking the right questions and increasing learning loop speeds. And it will allow us to then scale that knowledge faster through decision support systems. As the biggest supplier of maritime process equipment, Alfa Laval, we use our knowledge and experience daily to improve our customers processes. AI being an exponential enabler of speed and scale, it is among the tools we use to scale our knowledge, helping us to go even deeper and wider for the benefit of our customers.
Dr. Nikos Loukeris Lecturer, Hellenic Open University in Finance; Adjunct Lecturer, Athens University of Economics & Business in Banking
The major problems today in the shipping industry that AI can solve are many and include: shortage of human work-force replaced with AI-robotic applications; management of environmental protective equipment and devices to meet new environmental regulations; cybersecurity which can be met with upgraded image and voice recognition, threat detection and cyber risk protection; costs can be controlled and diminished under thorough applications of AI in various phases of the business cycle; the larger size of vessels which can be faced by creating intermediate size vessels that supply the containers of dry/wet cargo to the terminal ports, supported by AI models that reduce costs; and finally the losses of distressed shipping companies can be restricted with AI applications that make the complicated processes of decision making more logical thus offering an effective corporate performance. Microsoft is creating a new AI application in SE Asia with a large team of experts to support the shipping industry, so in very short time it will be introduced in business practice.
Dr. Nikos Loukeris has a PhD in Artificial Intelligence and Finance, currently lectures at the University of South Wales and the University of Nicosia and has taught at universities in the US and Greece. He will be teaching the Lloyd’s Maritime Academy course: “Certificate in Artificial Intelligence in Shipping: Understand the role AI plays in the future of Shipping” starting this December 4, 2018. Learn more about Dr. Loukeris and the course here.
Douglas Diggle, CEO of Product & Brand Management, AOG & Company @DouglasDiggle
Cruise lines are usually years behind land-based hotels but with the industry building a record number 117 new vessels, new automated and smart processes are allowing data-driven decision making leads to greater marketing efficiency and a total guest experience. This is giving brands a competitive advantage and increased on board revenues. Many of us have a virtual personal assistant at home and now we have cruise vessels integrating innovative voice activated conversation tools that use artificial intelligence to intelligently communicate, learn about guests, and predict the needs of passengers, as well as to suggest interesting recommendations. As soon as 2019 you can have a personalized experience on board where passengers can communicate with the digital assistants in English, French, Italian, Spanish, German, Brazilian Portuguese and Mandarin.
Nidhi Gupta, Co-founder & Director, Portcast
In my view, the biggest problem for the shipping industry right now is the inefficient use of data. To give a concrete example, today if we purchase an airline ticket, it’s a dynamic price based on demand and supply that the airline estimates. If we ship cargo though, it’s still a largely intuitive and relationship-based decision. This is because the maritime industry is still making decisions based on historical data, market averages and intuition. And because the industry is highly prone to external disruptions (like weather, trade markets, geopolitical environment), it leads to immense fire fighting. This is where Portcast is helping maritime companies like shipping lines, forwarders and ports, to combine their historical data with external real-time datasets (economic, climate, sentiment and geospatial) and use advance machine learning to help make predictions of demand and cargo flows more accurate and ultimately pricing decisions more profitable.
Michael Johnson, Founder & CEO, Sea Machines @SeaMachines
The maritime industry today is highly manual and has a relatively high accident rate, largely due to human error. Sea Machines recognizes one solution to this includes deploying advanced perception and situational awareness technology, using Artificial Intelligence powered by deep learning aboard commercial ships. Such technology is closer than many realize: Sea Machines will trial it starting in Q4 aboard a Maersk container ship. This product is expected to improve at-sea situational awareness, object identification and tracking, and will provide intelligent information directly to the wheelhouse. Ultimately it will increase the safety, predictability and productivity of real-world shipping operations.
Constantine Komodromos, Co-Founder & CEO, Vesselbot @Vesselbot
In my opinion there is not just one big problem that artificial intelligence can solve but a large number of these that the industry faces in its day to day operations. The fact that our industry lags behind other markets in regards to the way it utilizes advanced technology makes it uncompetitive and outdated. Technology could assist it to operate in a more optimized and efficient way.
VesselBot, in association with a large Ship Owner has proven that AI can significantly enhance fleet performance in regards to TCE significantly. Shipping companies usually look to optimize the performance of each vessel separately rather than looking at the entire Fleet optimization. By utilizing AI millions of instantaneous, real time calculations and screening of variables – something that humans aren’t capable of doing which AI does – can enable companies to achieve better results in regards to their Fleet TCE.
Bjørn Haugland, Chief Sustainability Officer, DNVGL @BjornKHaugland
We see that data driven compliance may drive efficiency and transparency throughout the supply chain. Insights from data and data driven models along with ledger technologies may gradually replace physical inspections, document reviews, certificates and greatly impact the regulatory frameworks.
The move towards autonomy will completely depend on data and data driven modellings and have the potential to improve safety at sea and reduce environmental impact.
Data driven modelling may also contribute significantly to reduce fuel consumption and emissions through enabling more optimal commercial operations as well as efficiency management of the individual vessels.
DNV GL is deeply engaged with the shipping community to ensure safe and sustainable adoption of the new technologies through e.g. establishing recommended practices for verification of algorithms and data value chains in areas like safety management, energy efficiency and digital compliance.
Inna Kuznetsova, President & COO, INTTRA @InnaKuznetsova_
The use of chatbots for simple help in electronic transactions and operations are the low-hanging fruit right now, followed by the use of Artificial Intelligence (AI) in more complex areas such as global trade compliance. INTTRA is already incorporating chatbots with some of our new products such as C-FAST - an automated container forecasting and allocation solution that optimizes expected shipment volumes with carrier contractual agreements. We also leverage machine learning to enrich data in such services as ocean schedules. Going forward, the industry will see more of standardized operations fully automated with the help of AI - from accounting and billing to capacity planning, cargo visibility and global trade compliance.
Tor Jakob Ramsøy, CEO, Arundo Analytics @ArundoAnalytics
The two categories for which AI holds the most viability as a solution include individual vessel performance and fleet optimization. In terms of improving individual vessel performance, AI can be leveraged to optimize fuel and resource efficiency, manage emissions, improve system uptime and drive predictive maintenance. For fleet optimization, AI can be used to optimize scheduling and logistics in real time, as well as determine the fastest and most efficient shipping routes. In May, Arundo partnered with DNV GL’s Veracity, an open and secure platform providing an interface for shipping professionals and organizations to access technology, data and services from key providers in the maritime space. Through the Veracity platform, Arundo provides end-to-end data analytics for several fleets, including streaming data from ships en route, providing offline analytics capabilities, and insights in categories like performance forecasting for vessels.
In 2016, Arundo also worked with Carnival Maritime, leveraging machine learning and their own domain expertise to determine how much potable water the ship needed to have on board, while minimizing costs and fuel consumption. Arundo’s machine learning-driven solution incorporated data from sources like the ship’s passenger manifest, routes and distillation capacity.
Dino Mandić, Founder, SailRouter B.V, @mandulhr
Today the biggest challenge for the shipping industry is to analyze a huge amount of data collected during ship navigation in order to learn about ship behavior on waves. The main target of that is to use historical ship data to optimize the next voyage. Any data analysis is a more suitable task for artificial intelligence than for humans, especially when an output must be issued very fast. Current ship technology enables collecting data from sensors about every piece of important onboard information but there is no sensor which can measure sea waves during navigation. Our approach is to use artificial intelligence to recognize sea waves during navigation based on ship motions.
Valentin Perret, Head of Business, Shone, @ShoneAutomation
One of the biggest challenges the shipping industry is facing right now is an information problem. There is too much information available onboard ships for the crew to be able to take the best decision at the right time. Yet, ship operators only have incomplete bits of information reported to them from the ships.
With CMA-CGM we use artificial intelligence to map their ship environment and display only relevant information to the navigating crew at the right time while providing comprehensive real time data to their fleet center. This solves the information overload for the crew while allowing the fleet center to better optimize their operations.
Nick Chubb, Head of Growth, CargoMate, Founder, Antares Insight, @NaChubb
By far the biggest problem AI can solve within the maritime industry is security - both physical and cyber. It's still too easy for criminal gangs to smuggle illicit goods or weapons across borders by sea and as we embrace digitalization, cyber attacks on maritime infrastructure will only increase. It's not currently possible for every single person or vehicle that enters a port to be properly checked. But AI powered security platforms are able to monitor vessel movements, customs declarations, and even CCTV footage to flag up suspicious behaviour to security teams. UK startup Zasti uses a powerful deep learning algorithm to recognise suspicious people from CCTV feeds. It can flag up known suspects to human security teams and even predict criminal behaviour based on the actions and facial expressions of people captured on video. Another UK startup, DarkTrace, has developed an AI based cyber immune system which automatically learns to spot cyber attacks and shut them down as quickly as possible.
Ready to be an early adopter at your organization? Lloyd’s Maritime Academy’s “Certificate in Artificial Intelligence in Shipping” provides 12 weeks of tutored distance learning where you’ll get the basics of artificial intelligence, from artificial neurons to MLP (multilayer perceptrons). This artificial intelligence course will provide you with training on everything you need to know from data preprocessing and Heuristics, Evolutionary Computation (GA) to Hybrids. Most importantly you’ll learn about real-life AI applications for navigation, cargo, purchasing, costs, telecommunications and security. Learn more about our course on artificial intelligence in shipping today.