VesselAI Project Factsheet
ENABLING MARITIME DIGITALIZATION BY EXTREME-SCALE ANALYTICS, AI AND DIGITAL TWINS
Project description
New platform to promote digitalisation in the shipping industry
The digital twin concept, a virtual representation of a physical asset that can be used as a model for various purposes, is making waves in a range of industries. The shipping sector is no exception. The EU-funded VesselAI project plans to develop a framework that facilitates the modelling and prediction of ships' behaviour. Using digital twin technology, the framework will efficiently fuse and assimilate huge amounts of data, enabling highly accurate modelling as well as design and operation optimisation of ships and fleets under various dynamic conditions. VesselAI will also tap into the potential of artificial intelligence, cloud computing and high-performance computing, encouraging deeper digitalisation in the shipping industry.
Objective
Shipping is the lifeblood of global economy, consequently one of the leading sources of greenhouse gases and one of the high-incident domains, due to heavy traffic especially in congested waters, therefore facing escalating pressure for safety, energy efficiency improvement and emissions reduction. Meanwhile, shipping generates extremely large amount of data in every minute, which potential, however, still remains untapped due to the involvement of enormous stakeholders and the sophistication of modern vessel design and operation. To address these challenges, VesselAI aims to develop, validate and demonstrate a unique framework to unlock the potential of extreme-scale data and advanced HPC, AI and Digital Twin technologies, and hence to promote the adoption and application of Big Data-driven innovations and solutions in maritime industry and beyond. By combining Digital Twin technologies and practices, VesselAI can efficiently fuse and assimilate huge amount of data, coming from both observations and simulations, to achieve highly accurate modelling, estimation and optimization of design and operation of ships and fleets under various dynamic conditions in near real time. Their technical enhancements and practical performance improvements are further demonstrated in 4 maritime industry pilots, tackling practical challenges for 1) global vessel traffic monitoring and management, 2) globally optimal ship energy system design, 3) short-sea autonomous shipping and 4) global fleet intelligence. VesselAI brings in a consortium of renowned actors in maritime and ICT domains, providing a perfect mix of high-level expertise in both domains and readily accessibility to huge amount of data for industry-leading research and innovation in the project. Together, VesselAI addresses the challenges of implementing extreme-scale analytics in industries and showcase how AI, cloud computing and HPC can encourage, and enable deeper digitalization in the maritime and wider industries.
Programme
Topic
ICT-51-2020 - Big Data technologies and extreme-scale analytics
Project Information
VesselAI
Grant agreement ID: 957237
DOI
10.3030/957237
Start Date
January 1st, 2021
End Date
December 31st, 2023
Funded under
INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (H2020-ICT-2020-1)
RIA - Research and Innovation Action
€ 5 998 877,50
Coordinated by
ETHNICON METSOVION POLYTECHNION (NTUA) - Greece