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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.

Call for proposal

H2020-ICT-2018-20

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Sub call

H2020-ICT-2020-1

Coordinator

ETHNICON METSOVION POLYTECHNION
Net EU contribution
€ 511 562,50
Address
HEROON POLYTECHNIOU 9 ZOGRAPHOU CAMPUS
157 80 ATHINA
Greece

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Region
Αττική Aττική Κεντρικός Τομέας Αθηνών
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 511 562,50

Participants (12)