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Sorry, what did you say? Bjørn Åge Hjøllo, chief sustainability officer at e-navigation specialist NAVTOR, smiles in recognition of the obvious disbelief. He tries again: “I said that this project has the potential to cut 1% of all global emissions.” 1% of all shipping emissions? “No, 1% of total global emissions… for everything.” This may be the first, but it won’t be the last, time Hjøllo is met by someone that needs to reboot their brain while struggling to comes to terms with the ambition of the Norwegian government backed Green AI for Sustainable Shipping (GASS) research project. Led by NAVTOR, the initiative is a partnership with Grieg Star, Maritime CleanTech, Scandinavian Reach Technologies (ScanReach), Simula Research Laboratory, SinOceanic Shipping, and Sustainable Energy/SIVA, with support from the Norwegian Research Council, Innovation Norway, and SIVA. Over the course of the next three years, it aims to champion what Hjøllo calls a “data driven approach to decarbonisation” enabling shipping companies to identify, analyse and address inefficient energy use on any vessel, in any location, in any weather conditions, in real-time. At present, there are no systematic data‐driven solutions for improving energy efficiency onboard Powered by machine learning algorithms, digital twin technology, and a constant stream of high-quality data, the end result will be, says Hjøllo, “a simple, powerful decision-making tool that allows users to maintain competitiveness, achieve regulatory compliance and, in short, unlock more sustainable shipping.” Although he makes it sound easy there’s a lot of hard work that needs to be done first. “At present, there are no systematic data‐driven solutions for improving energy efficiency onboard, and GASS aims to address that,” Hjøllo says. “We want to capture granular information from a very wide range of high frequency data that basically allows us to predict what a vessel’s fuel consumption should be, regardless of vessel type, location, weather and so on. That means integrating precision data from vessel operations and exact operating environments - combining MetOcean condition and forecast data, AIS data, and a whole range of reporting and performance data gathered in real-time, all the time, from sensors. That can span anything ranging from propellor information, to engine RPMs, navigational data, speed and so on.” Once they have this building material, Hjøllo explains, it can be used to craft a digital twin of any vessel that, regardless of operational parameters, can be used to demonstrate optimal fuel consumption. If the ‘real world’ ship is failing to live up to its virtual sibling’s performance, then the data can be instantly analysed to find out why. “Maybe there’s an issue with the trim of the vessel, or a problem with fouling, or perhaps the auxiliary engine has been used in a congested area and it’s still running when there’s no need,” he says. “With much richer, real-time data than ever before, we can unlock up to the minute awareness and performance analytics that enable dynamic voyage optimisation – as opposed to today’s static standard – and allow onshore teams and onboard crews to address issues/deviations from plans as they actually happen. That’s an incredibly powerful advantage to have, especially in the new regulatory reality of CII ratings and EU ETS, for example, and the associated costs and investments associated with compliance. This could be huge.” Once extensive testing and validation has been completed, the AI module will be integrated into NAVTOR’s existing, joined-op portfolio. Although it’s early days, Hjøllo suggests that this would be on both NavStation (the company’s onboard digital chart table/planning system) and NavFleet (a shore-based management, monitoring and optimisation solution) allowing both vessel and office teams to make the most of up-to-the-minute insights and enhance decision making. It’s the impact on emissions that should create the greatest excitement, argues Hjøllo. Bringing us back to that 1% figure. How is that possible? Hjøllo admits that the number is both a best and worst case forecasted scenario. Here’s how the GASS partners arrived at it. Today, worldwide shipping accounts for nearly 3% of greenhouse gas emissions. However, widely reported research suggests that it could reach as much as 17% by 2050 as global trade expands and other industries cut emissions faster than maritime. GASS expects that a machine learning application that dynamically optimises vessel energy use should be able to reduce consumption, and therefore GHG emissions, by 20%. So, when the 30%+ of vessels in the world fleet that use NAVTOR products have their breakthrough AI technology powered up, that translates to over a 5% cut in all of shipping’s emissions and (assuming the 17% figure) a 1% cut in total global emissions. Hjøllo can’t supress a smile, but is cautious enough not to get carried away. “I think the important thing is there’s nothing to suggest we can’t do this – we, and our partners, have the track record, technology, and domain expertise to succeed here. The 1% figure obviously depends on a lot of variables that are beyond our control, but the 20% reduction per vessel doesn’t. That is a very realistic target.” He concludes: “If we can play a part in reducing energy use and emissions by one fifth on every vessel we serve – regardless of type, age, location, weather, whatever – imagine how powerful that could be. Imagine the difference environmentally, from a regulatory perspective and commercially.”

How one maritime AI research project could cut 1% of total global emissions

Bjørn Åge Hjøllo, chief sustainability officer at Norway’s NAVTOR, on a hugely ambitious project to help save the planet

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