ABOUT VesselAI

VesselAI aims at realising a holistic, beyond the state-of-the-art AI-empowered framework for decision-support models, data analytics and visualisations to build digital twins and maritime applications for a diverse set of cases with high impact, including simulating and predicting vessel behaviour and manoeuvring (including the human factor), ship energy design optimisation, autonomous shipping and fleet intelligence

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Open & Trusted Platform

Deliver an open and trusted platform capable of distributed data analysis workflows combining data-intensive capabilities, fuelling shore-side decision support and next-generation maritime services

Components for Extreme-scale Data

Design and develop the appropriate software and hardware components, tools and libraries that will enable the efficient ingestion, curation and querying of extreme-scale data sets coming from different sources

High-quality ML/DL Models

Deliver a set of trained, high-quality interpretable ML / DL models by exploiting extreme-scale data sets for advanced classifications, analysis and forecasts related to maritime entities

HPC & Resource Management

Deliver a state-of-the-art HPC and resources management framework for optimising the required extreme-scale data processing, models training and serving for maritime digital twins and applications

Demonstrate the value of VesselAI

Demonstrate the applicability and value of the VesselAI framework, models and tools through real-life maritime digital twins and applications

Support European Research in AI

Support European Research in AI by utilising, contributing to and extending the AI4EU platform services and research activities

Promotion & Adoption of VesselAI

Promotion and adoption of the outcomes to maritime-related organisations across the EU, as well as to stakeholders involved in the scientific areas of AI, HPC and Big Data

Exploitation of the VesselAI Platform

Development of a comprehensive business plan that will guarantee the exploitation and sustainability of the VesselAI research, platform, and its services beyond the end of the project

13

Consortium Members

6

Countries

4

Pilots

3

Years

VesselAI Pilots

Designing and developing a high-performance, scalable and sustainable decision-making framework for data-driven digital twins includes and requires innovation diffusion and exploitation of network dynamics, and the adaptability to the stakeholders’ needs. In this direction, VesselAI brings a diverse set of pilot scenarios to the centre of the process, to test and improve the initial proposition, and provide a truly innovative solution that makes extreme-scale decision analysis, using novel data engineering and machine learning techniques, a native engineering characteristic

VesselAI researches and extends different models for feeding Vessel Traffic Management Systems and experimental digital twins of the vessels using different Machine and Deep Learning approaches

VesselAI incorporates AI, HPC and digital twin in the loop of the design and optimization process to effectively simulate and optimize thousands of design alternatives for ship energy systems

VesselAI utilises large volumes of data from shore control centres to forecast traffic situations beyond the next manoeuvre and to predict the next manoeuvres of the surrounding manned vessels

VesselAI provides an AI-based realtime fleet operations optimization using vessel and fleet digital twins, with automated voyage optimization, according to weather and operations

VesselAI Blog / News

Get to know the latest news about VesselAI

Meet our Team

Led by well-experienced enterprises and institutions, the VesselAI project is bound to introduce notable advancements beyond the state of the art, with the research partners contributing a promising blend of data engineering, artificial intelligence, HPC, simulations and maritime technology and the pilot partners providing their requirements, innovative use-case testing and end-user engagement and validation.

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Dimitris Askounis

Project Coordinator

Professor @ National Technical University of Athens

Dimitris Askounis

Project Coordinator

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Spiros Mouzakitis

Technical Coordinator

Research Analyst @ National Technical University of Athens

Spiros Mouzakitis

Technical Coordinator

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Dimitris Zissis

Quality Manager

Assoc Professor @ University of the Aegean, MarineTraffic

Dimitris Zissis

Quality Manager

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Jukka Nurminen

Innovation Manager

Professor @ University of Helsinki

Jukka Nurminen

Innovation Manager

Consortium Partners

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