Metrology for Maritime Transport, Ports and Shipping


Fiorini Michele Fiorini

Michele Fiorini

Leonardo S.p.A., Italy

Jillian Jillian Carson-Jackson

Jillian Carson-Jackson

The Nautical Institute, UK

Zissis Dimitris Zissis

Dimitris Zissis

University of Aegean, Greece


The topic of this workshop is metrology for the ocean environment, involving the design development and integration of complex sensor systems for maritime and ocean surveillance.

This special session aiming to further sharing knowledge, exchange of ideas and proposals on latest researches and practical applications for maritime surveillance and transport systems, ports and shipping. On field measurements and applications, practical experiences from real world systems are particularly welcome as well as novel theories and academic researches.

The workshop will provide the space for the wider research and end-user community to interact and discuss future opportunities and challenges. Engineers, technicians, industrial directors, students, professors, researchers as well as people working on the Administrations, VTS experts, pilots, coast guards and navy personnel at all levels and any stakeholders working on maritime transport, ports and shipping can contribute making knowledge, familiarise, exchange ideas and create further cooperation.


Possible topic are, but not limited to:

  • Vessel Traffic Services (VTS);
  • Coastal Surveillance Systems (CSS);
  • E-navigation;
  • Tracking Systems;
  • Satellite Surveillance and Communications;
  • Digitalisation;
  • Information and Communications Technology (ICT) Solutions;
  • Cybersecurity;
  • Autonomous Vessels and Drone Ships;
  • Maritime Simulations Systems;
  • Maritime Training Systems;
  • Maps and Cartography;
  • Prototype Components and Systems;
  • Ports Logistics;
  • Ports and shipping tourism;
  • Systems Integration and Commissioning;
  • Maritime Informatics;
  • Digital communications supporting vessel tracking and autonomous vessel operations;
  • Seafarer Recruitment and Ship Crew Management;
  • Anything else related to the Maritime Sector.


Michele Fiorini, MBA, PhD, CEng, FIET, SMIEEE educated at Ancona (Italy), Bath (United Kingdom) and Gdańsk (Poland) Universities, holds a Ph.D. in electronic and telecommunications engineering in Italy and an M.B.A. in strategy, programme and project management in Poland. He is an engineering manager at Leonardo s.p.a. in Rome (Italy) where he is providing technical and management leadership on maritime transport and border control systems.
Dr Fiorini has been Product Owner (Consortium Leader) for the realisation of the “Zautomatyzowany System Radarowego Nadzoru (ZSRN) polskich obszarów morskich / Automatic National System of Radar Control for Maritime Areas of Poland” realized by Selex – Sistemi Integrati (now Leonardo s.p.a.) in consortium with local partners (2012-16). In June 2018 he was invited to provide special lecture and advices at Mokpo National Maritime University (MMU), Republic of Korea on how to solve navigational risk based on vulnerability of maritime accidents for e-Navigation. In 2021 he joined the European team of experts working on the implementation of the European Defence Industrial Development Programme (EDIDP), established by Regulation (EU) 2018/1092 of the European Parliament and the Council, aiming at supporting the competitiveness and innovation capacity of the European Union's (EU’s) defence industry. For 2023-24 Dr Fiorini is member of the Italy delegation to NATO Industrial Advisory Group (NIAG), an high-level consultative and advisory body of senior industrialists of NATO member countries.
Dr Fiorini has been a Session Chair at the 2013 Euro-Asia Economic Forum in Xi’an, China; Chair of Council at the Institution of Engineering and Technology (IET) in London, 2017-‘18; and Chair of Judges for the Chief Engineer of the Year Award at the IET Excellence and Innovation Awards 2023 in Glasgow (UK).

Jillian Carson-Jackson, B.ED, FNI, FRIN has over three decades of experience in the maritime environment, promoting education, training, diversity and inclusion. With practical experience both afloat and ashore, she has management experience in different government areas, including aids to navigation (AtoN), Vessel Traffic Services (VTS), regulation of maritime pilots, vessel tracking and maritime technology related fields. Through a varied career, Jillian has worked at the operational, technical, policy and legislative level. This includes work with the International Maritime Organization (IMO), International Telecommunication Union (ITU), International Electrotechnical Commission (IEC), and the International Association of Marine Aids to Navigation and Lighthouse Authorities (IALA) in addition to her work with the Canadian Coast Guard and the Australian Maritime Safety Authority. She currently manages her own maritime consultancy, providing a focus on technical advice, maritime education and training, and port risk assessment.
Jillian is the chair of the IALA ENAV Committee WG 2 (emerging digital technologies) and the IALA VTS Committee WG3 (Training and Personnel). She was recently appointed a director of GlobalMET and is the Past-President of the Nautical Institute.

Dimitris Zissis is an Associate Professor of Information and Communication Systems, at the Dept. of Product & Systems Design Engineering, University of Aegean (Greece), Head of the Intelligent Transportation Systems Lab and Director of the Postgraduate Programme “Maritime Robotics & Informatics”. He is currently the National Representative to the Horizon Europe Programme Committee (PC) for “Cluster 4: Digital, Industry and Space”, while he has been a member of the High Level Expert Groups on“Business-to-Government Data Sharing” and “Facilitating the use of new data sources for official statistics”. His professional experience includes several senior leadership positions in the deep tech industry. His academic work has been published in more than 100 research papers, while the focus of his publications is on Information and Communications Systems, Big Data, AI and Machine Learning.