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Description
The R&D project consists in the development of an innovative AI driven software solution to optimise vessels’ voyages for bulk carriers, based on low-frequency vessel data to decrease fuel consumption and emissions. It will comprise of a cloud software platform relating to voyage optimisation, by way of suggested voyage routes taking into consideration weather forecasts, the vessel''s specifications, and the results of artificial intelligence algorithms and accepting low-frequency data (noon- reports generated by the vessel''s crew and AIS data) utilising it to provide optimised voyage planning, as well as voyage monitoring and post voyage reporting. The project aims to make tangible steps towards the ambitious decarbonization goals set for the shipping industry. The promoter will collaborate with 2 partners from Norway, one research institute (SINTEF) and one commercial partner (G2Ocean), in order to bring to the market a well-rounded and tested product, ready for adoption. The project will lead to an increase in the profitability of the company, as well as contribute to obtaining a distinct competitive advantage.
Summary of project results
The project aimed at making tangible steps towards the ambitious decarbonization goals set for the shipping industry by the International Maritime Organisation (IMO), which requires the industry to achieve a 50% reduction of GHG emissions by 2050 and a 70% reduction of carbon intensity. Methodologies for improving carbon efficiency at the technical design level of vessels tend to entail very high CAPEX and yield uncertain impact on emission reduction. As a result, adoption is slow and shipping companies are running behind on their decarbonisation targets. Improving operational efficiency through digital optimization solutions present a large opportunity for fast, low CAPEX emissions reductions with high quantifiable impact on vessel efficiency and emissions. This project aimed at breaking this deadlock by developing a digital solution to optimise vessels'' voyages providing route and speed policies towards achieving decarbonisation.
The project''s core purpose was to reduce CO2 emissions by a direct fuel consumption reduction on every voyage/ drive down carbon emissions in their operations, via AI-voyage optimisation. 4 main activities were carried out. An analysis of the end-users'' needs were assessed and the product was designed. During the product development, tasks related to data/existing systems integration were implemented and the AI models, the optimisation algorithms, the back-end services and the User Interface were developed. Furthermore, an analysis of how maritime organisations operate on routing decisions was done.
The environmental impact of the digital solution was also assessed, to calculate CO2 reductions. The solution/system was applied to five bulk carriers (within G2Ocean''s fleet), in order to pilot the AI model and demonstrate its ability to produce accurate and optimised guidance to reduce fuel consumption and achieve the highest possible Time Charter Equivalent (TCE) for any given voyage.
The project also focused on breaking down barriers to the adoption of AI recommendations by the crew, ensuring high compliance with the AI-driven optimization.
As a result, a complete and tested product/solution, was developed ready for adoption.
Through the project, a digital solution was developed, aimed at driving decarbonisation in shipping. This AI method means that the benefits of high-frequency, real-time data can be harnessed by vessels that don’t have sensors (for example, those using noon reports) with a level of accuracy that is very close to that of high-frequency vessels. This helps operators to reduce fuel consumption and lower emissions, breaking down barriers for adoption with no need for hardware installation.
The Pythia Light solution was developed specifically for bulkers, a vertical not yet penetrated by any of Deepsea’s solutions. Bulk carriers represent approximately 10% of the world fleet, and 33% of the world gross tonnage. The project will thus lead to an increase in the profitability of the company, as well as contribute to obtaining a distinct competitive advantage.
Summary of bilateral results
This was a very good partnership project as both donor partners contributed to the successful implementation of the project. In addition, the project led to the increase and sharing of knowledge between entities, towards a common result. SINTEF, a leading independent research organisation, identified the needs of users and carried out a detailed mapping of the process of adoption of the technology; it investigated what could prevent AI solutions to be implemented in the shipping industry. Breaking down barriers to the adoption of AI recommendations by the crew is essential, as the value of AI-driven optimisation to sustainable shipping operations can only truly be realised if there is high compliance with the recommendations produced. With this project, Sintef will gain knowledge about the process of AI-based applications in the maritime sector.G2Ocean, a shipping company, tested the solution on its fleet; it provided the vessels'' datasets and identified users'' requirements.G2Ocean will also be the first client of the developed solution (so the partnership will continue beyond this project). Prior to this project, DeepSea was trying to contact Sintef in order to collaborate. This project provided an opportunity to cooperate, and it seems that this cooperation could continue in the future.