Innovative cognitive data platform to improve processes in European seaports
The DataPorts project aims to provide a data sharing platform with Artificial Intelligence capabilities for the different actors that operate in a port environment. The platform is being validated in two local demonstration sites (Valencia and Thessaloniki), where it offers data driven services to relevant stakeholders, addressing concrete problems. Additionally, the platform is being tested in two global use cases where it has been integrated with commercial platforms and tools. In this paper, several scenarios of the pilots are presented and the benefits of the DataPorts platform in each scenario are discussed.
- Record URL:
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/23521465
-
Supplemental Notes:
- © 2023 The Author(s). Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
-
Authors:
- Belsa, Andreu
- Julian, Matilde
- Calciati, Paolo
- Cáceres, Santiago
- Gizelis, Christos
- Nikolopoulos-Gkamatsis, Filippos
- Nestorakis, Konstantinos
- Giménez, Pablo
- Clemente, José Antonio
- Iturria, Héctor
- Palau, Carlos E
-
Conference:
- Transport Research Arena Conference (TRA Lisbon 2022)
- Location: Lisbon , Portugal
- Date: 2022-11-14 to 2022-11-17
- Publication Date: 2023
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 1232-1239
-
Serial:
- Transportation Research Procedia
- Volume: 72
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 2352-1465
- Serial URL: http://www.sciencedirect.com/science/journal/23521465/
-
Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Artificial intelligence; Business models; Data management; Data sharing; Port operations; Seaports
- Geographic Terms: Europe
- Subject Areas: Data and Information Technology; Marine Transportation; Terminals and Facilities;
Filing Info
- Accession Number: 01911225
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 8 2024 3:32PM