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VesselAI

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ENABLING MARITIME DIGITALIZATION BY EXTREME SCALE ANALYTICS AI AND DIGITAL TWIN...

ENABLING MARITIME DIGITALIZATION BY EXTREME SCALE ANALYTICS AI AND DIGITAL TWINS 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 pressu... ver más

31/12/2023

NATIONAL TECHNICAL...

6M€

Presupuesto del proyecto: 6M€

Líder del proyecto

ETHNICON METSOVION POLYTECHNION No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 13 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2023-12-31

ICT-51-2020: Big Data technologies and extreme-s... Specific Challenge:Rapidly increasing volumes of diverse data from distributed sources create challe...

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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No hay información privada compartida para este proyecto. Habla con el coordinador.

13 Participantes

NATIONAL TECHNICAL UNIVERSIT...

511.56K€ | Lider

CONSULTING INFORMATICO DE CA...

153.85K€ | Participante

UNINOVA

540.38K€ | Participante

UNIVERSITY OF PIRAEUS

296.25K€ | Participante

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Duración del proyecto: 41 meses Fecha Inicio: 2020-07-28
Fecha Fin: 2023-12-31

Líder del proyecto

ETHNICON METSOVION POLYTECHNION No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 6M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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.

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