Open collaboration and open Digital Twin infrastructure for Green Smart Shipping

Informations projet

DT4GS

N° de convention de subvention: 101056799

DOI

10.3030/101056799

Projet clôturé

Date de signature de la CE 28 Avril 2022

Date de début 1 Juin 2022

Date de fin 31 Mai 2025

Financé au titre de

• Climate, Energy and Mobility

Coût total

€ 6 987 333,00

Contribution de l’UE

€ 6 987 331,00

Coordonné par

INLECOM GROUP
Belgium

CORDIS fournit des liens vers les livrables publics et les publications des projets HORIZON.

Les liens vers les livrables et les publications des projets du 7e PC, ainsi que les liens vers certains types de résultats spécifiques tels que les jeux de données et les logiciels, sont récupérés dynamiquement sur OpenAIRE .

Livrables

Other (4)

DT4GS (Green Shipping) Dataspace v1

Connectors Module 1st Version, IoT infrastructure, Internal and External Connectors matching selected priority use cases. This deliverable includes the outputs of T2.2.

DT4GS Model Blueprints and Open Model Library v1

Model blueprints template, and optimised models, Open Model Library (OML) prototype. This deliverable includes the outputs of T2.4.

DT4GS knowledge Hub v1

Observatory for GS Solutions first release. This deliverable includes the outputs of T3.1.

DT4GS Edge and Orchestration Infrastructure v1

Cloud based infrastructure for services provisioning, deployable library on vessels. Hosting and orchestration services including tools for deployment automation. This deliverable includes the outputs of T2.5.

Documents, reports (2)

DT4GS modelling framework for ship operational performance optimisation including ship efficiency innovations

Modelling Framework Specification, Navigation Management and hull models, Integrated Machinery Performance management and remote-control models, Integrated ship energy production models, Robust Fuel consumption models, and Life Cycle assessment Models. Model updates and Integrated modelling framework based on LL feedback. This deliverable includes the outputs of T1.2.

DT4GS Value-oriented Analysis in enabling Shipping Decarbonisation

Value Oriented Analysis, LLs Scenarios, Transition Challenges, and high-level scenarios Requirements. This deliverable includes the outputs of T1.1.

Websites, patent fillings, videos etc. (1)

Dissemination & Communication v1

Establish project communication and dissemination Strategy/Plan and report. This deliverable includes the outputs of T5.1.

Publications

Peer reviewed articles (9)

Knowledge Graphs underpinning ship digital twins for decarbonisation options assessment

Auteurs: Bill Karakostas; Antonis Antonopoulos
Publié dans: International Marine Design Conference, 2024, ISSN 3050-4864
Éditeur: IMDC
DOI: 10.59490/IMDC.2024.871

Ship Design in the Era of Digital Transition

Auteurs: Apostolos Papanikolaou, Evangelos Boulougouris, Stein-Ove Erikstad, Stefan Harries, Austin A. Kana
Publié dans: International Marine Design Conference, 2024, ISSN 3050-4864
Éditeur: TU Delft OPEN Publishing
DOI: 10.59490/IMDC.2024.784

Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning

Auteurs: Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis
Publié dans: Journal of Marine Science and Engineering, Numéro 13, 2025, ISSN 2077-1312
Éditeur: MDPI AG
DOI: 10.3390/JMSE13050902

Trajectory Mining and Routing: A Cross-Sectoral Approach

Auteurs: Dimitrios Kaklis; Ioannis Kontopoulos; Iraklis Varlamis; Ioannis Z. Emiris; Takis Varelas
Publié dans: Journal of Marine Science and Engineering, 2024, ISSN 2077-1312
Éditeur: MDPI
DOI: 10.3390/JMSE12010157

Digital twin for ship life-cycle: A critical systematic review

Auteurs: F. Mauro, A.A. Kana
Publié dans: Ocean Engineering, Numéro Article 113479, 2023, ISSN 0029-8018
Éditeur: Pergamon Press Ltd.
DOI: 10.1016/j.oceaneng.2022.113479

Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning

Auteurs: Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis
Publié dans: Journal of Marine Science and Engineering, Numéro 13, 2025, ISSN 2077-1312
Éditeur: MDPI AG
DOI: 10.3390/JMSE13050902

Agentic AI for Digital Twin

Auteurs: Alexander Timms, Abigail Langbridge, Antonis Antonopoulos, Antonis Mygiakis, Eleni Voulgari, Fearghal O'Donncha
Publié dans: Proceedings of the AAAI Conference on Artificial Intelligence, Numéro 39, 2025, ISSN 2374-3468
Éditeur: Association for the Advancement of Artificial Intelligence (AAAI)
DOI: 10.1609/AAAI.V39I28.35373

Enabling digital twins in the maritime sector through the lens of AI and industry 4.0

Auteurs: Dimitrios Kaklis, Iraklis Varlamis, George Giannakopoulos, Takis J. Varelas, Constantine D. Spyropoulos
Publié dans: International Journal of Information Management Data Insights, Numéro Article 100178, 2023, ISSN 2667-0968
Éditeur: Elsevier Ltd
DOI: 10.1016/J.JJIMEI.2023.100178

Retrofit modeling for green ships

Auteurs: Julien J. M. Hermans; Austin A. Kana
Publié dans: International Marine Design Conference, 2024, ISSN 3050-4864
Éditeur: IMDC
DOI: 10.59490/IMDC.2024.890

Conference proceedings (10)

Agentic AI for ship routing

Auteurs: Fearghal O'Donncha, Abigail Langbridge, Alexander Timms, Antonis Antonopoulos, Antonis Mygiakis, Eleni Voulgari
Publié dans: 2025
Éditeur: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-19197

Applying Hybrid Quantum LSTM for Indoor Localization Based on RSSI

Auteurs: S.F. Chien, David Chieng, Samuel Y.C. Chen, Charilaos C. Zarakovitis, H. S. Lim, Y.H. Xu
Publié dans: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024
Éditeur: IEEE
DOI: 10.1109/ICASSP48485.2024.10447032

A Digital Twin Enabled Decision Support Framework for Ship Operational Optimisation Towards Decarbonisation

Auteurs: Antonis Antonopoulos, Bill Karakostas, Takis Katsoulakos, Anargyros Mavrakos, Theodosis Tsaousis, Stathis Zavvos
Publié dans: Proceedings of Eighth International Congress on Information and Communication Technology (ICICT 2023), 2023, ISSN 2367-3370
Éditeur: Springer
DOI: 10.1007/978-981-99-3091-3_38

Agentic Anomaly Detection for Shipping

Auteurs: A Timms, A Langbridge, F O'Donncha
Publié dans: NeurIPS 2024 Workshop on Open-World Agents, 2024
Éditeur: NeurIPS 2024 Workshop on Open-World Agents

Optimal Transport for Efficient, Unsupervised Anomaly Detection on Industrial Data

Auteurs: Abigail Langbridge, Fearghal O’Donncha, James T Rayfield, Bradley Eck
Publié dans: 2024 IEEE International Conference on Big Data (BigData), 2025
Éditeur: IEEE
DOI: 10.1109/BIGDATA62323.2024.10825081

A Digital Twin Enabled Decision Support Framework for Ship Operational Optimisation Towards Decarbonisation

Auteurs: Antonopoulos, Antonis; Karakostas, Bill; Katsoulakos, Takis; Mavrakos, Anargyros; Tsaousis, Theodosis; Zavvos, Stathis
Publié dans: Proceedings of Eighth International Congress on Information and Communication Technology(ICICT 2023), 2023
Éditeur: SpringerLink
DOI: 10.1007/978-981-99-3091-3_38

Knowledge Graph Based Digital Twin to Support Green Shipping

Auteurs: Bill Karakostas, Antonis Antonopoulos, Takis Katsoulakos, Anargyros Mavrakos, Theodosis Tsaousis
Publié dans: CM3 – TRANSPORT 2023 : New Greener and Digital Modern Transport – its Challenges in Design Methods, Tools and Technologies : Book of Abstracts and Programme, 2024, ISSN 2670-191X
Éditeur: Jyväskylän yliopisto

Time Series Analysis for Digital Twins in Green Shipping

Auteurs: Lazaros Avgeridis; Konstantinos Lentzos; Dimitrios Skoutas; Ioannis Z. Emiris
Publié dans: SNAME 8th International Symposium on Ship Operations, Management and Economics, Numéro SNAME-SOME-2023-028, 2023, ISSN 0000-0000
Éditeur: OnePetro
DOI: 10.5957/SOME-2023-028

Quantum Neural Networks: A Path to Lower Emissions Through Fuel Consumption Prediction in Shipping

Auteurs: S.F. Chien, Julien J.M. Hermans, Austin A. Kana, Charilaos. C. Zarakovitis, Stathis Zavvos, H.S. Lim
Publié dans: ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025
Éditeur: IEEE
DOI: 10.1109/ICASSP49660.2025.10888871

From STEAM to Machine: Emissions control in the shipping 4.0 era

Auteurs: Dimitrios Kaklis, Takis J. Varelas, Iraklis Varlamis, Pavlos Eirinakis, George Giannakopoulos, Constantine V. Spyropoulos
Publié dans: SNAME 8th International Symposium on Ship Operations, Management and Economics, Numéro SNAME-SOME-2023-020, 2023
Éditeur: OnePetro
DOI: 10.5957/SOME-2023-020

Monographic books (1)

State-of-the-Art Digital Twin Applications for Shipping Sector Decarbonization

Auteurs: Bill Karakostas and Takis Katsoulakos
Publié dans: 2024
Éditeur: IGI Global
DOI: 10.4018/978-1-6684-9848-4