12. mars 2026
A newly published scientific review, Estimation and Optimisation of Ship Fuel Consumption in Maritime: Review, Challenges and Future Directions, offers timely insights that strongly support the GASS mission of reducing greenhouse‑gas emissions through data-driven optimisation in voyage planning and vessel operations.
The paper, authored by Dusica Marijan, Hamza Haruna Mohammed, and Bakht Zaman, presents a comprehensive overview of the current state of ship fuel‑consumption modelling and outlines clear pathways for advancing maritime sustainability.
The Growing Importance of Accurate Fuel‑Consumption Modelling
The study emphasises that fuel consumption is a major driver of both operational costs and emissions in global shipping. Improving fuel efficiency has therefore become increasingly critical as the maritime sector moves toward ambitious decarbonisation goals.
According to the authors, accurately estimating vessel fuel consumption is challenging due to its dependency on a wide range of dynamic factors, such as hull design, weather conditions, cargo load, and operational decisions.
A Structured Review of Modelling Approaches
The paper categorises the main modelling methods into three groups:
Physics‑based models, which rely on principles from naval architecture and hydrodynamics
Machine‑learning models, which learn patterns from historical and high‑resolution operational data
Hybrid models, which combine physical principles with data‑driven learning
Each approach has notable strengths, yet each also faces limitations. Physics‑based models may oversimplify reality, while data‑driven models depend heavily on data quality and availability. Hybrid models emerge as a promising direction, offering a balance of accuracy, robustness, and explainability.
Data Fusion and Explainable AI: Key Enablers for the Future
A significant contribution of the study is its emphasis on data fusion, which integrates multiple data sources—including AIS, onboard sensors, and meteorological information—to improve predictive performance. This aligns closely with the GASS project’s approach of leveraging high-volume, multimodal maritime datasets to enable more reliable optimisation of energy-efficient vessel operations.
The authors also highlight the rising importance of Explainable AI (XAI) in ensuring trust, transparency, and regulatory readiness for AI-driven decision support in shipping. This is especially relevant as AI solutions expand across fleets and must meet stringent safety and compliance expectations.
Challenges Identified and Recommendations for Future Research
Despite recent progress, several systemic challenges remain. The paper identifies the following key issues:
Inconsistent data quality, particularly for high-frequency sensor datasets
Limited generalisation of models across vessel types and operating environments
The need for real-time optimisation, which requires robust and scalable computation pipelines
Lack of standardised datasets, which restricts meaningful comparison between research outputs
To address these gaps, the authors recommend further development of hybrid models, improvements in the reliability and representativeness of maritime data, and increased efforts to standardise benchmarking datasets. These recommendations strongly resonate with GASS’s own objectives for enabling next-generation AI-driven optimisation and advancing maritime decarbonisation.
Relevance to the GASS Project
The paper’s findings reinforce the importance of the GASS project’s ongoing work to build data-driven, AI-enhanced technologies for reducing greenhouse‑gas emissions in the maritime sector. As GASS already recognises, traditional optimisation solutions often rely on sparse or simplified data and can therefore lead to suboptimal energy usage.
GASS leverages large-scale historical and real‑time datasets, machine learning, and advanced analytics to deliver improved energy efficiency, route optimisation, and compliance with evolving environmental regulations.
The insights presented in this new research offer valuable support and validation for the technical direction and ambitions of the GASS consortium as it continues to develop innovative solutions for sustainable shipping.
The Science Paper Authors
 Dusica Marijan |  Hamza Haruna Mohammed |  Bakht Zaman |
The GASS-project is made possible by The Green Platform Initiative (“Grønn Plattform”) funding scheme by Norges forskningsråd, Innovation Norway and Siva SF under the Grant Agreement No. 346603.