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  4. Towards Cognitive Ports of the Future
 
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2022
Book Article
Title

Towards Cognitive Ports of the Future

Abstract
In modern societies, the rampant growth of data management technologies - that have access to data sources from a plethora of heterogeneous systems - enables data analysts to leverage their advantages to new areas and critical infrastructures. However, there is no global reference standard for data platform technology. Data platforms scenarios are characterized by a high degree of heterogeneity at all levels (middleware, application service, data/semantics, scalability, and governance), preventing deployment, federation, and interoperability of existing solutions. Although many initiatives are dealing with developing data platform architectures in diversified application domains, not many projects have addressed integration in port environments with the possibility of including cognitive services. Unlike other cases, port environment is a complex system that consists of multiple heterogeneous critical infrastructures, which are connected and dependent on each other. The key pillar is to define the design of a secure interoperable system facilitating the exchange of data through standardized data models, based on common semantics, and offering advanced interconnection capabilities leading to cooperation between different IT/IoT/Objects platforms. This contribution deals with scalability, interoperability, and standardization features of data platforms from a business point of view in a smart and cognitive port case study. The main goal is to design an innovative platform, named DataPorts, which will overcome these obstacles and provide an ecosystem where port authorities, external data platforms, transportation, and logistics companies can cooperate and create the basis to offer cognitive services. The chapter relates to knowledge and learning as well as to systems, methodologies, hardware, and tools cross-sectorial technology enablers of the AI, Data and Robotics Strategic Research, Innovation & Deployment Agenda (Milano et al., Strategic research, innovation and deployment agenda - AI, data and robotics partnership. Third release. Big Data Value Association, 2020).
Author(s)
Cáceres, Santiago
Instituto Tecnologico de Informatica
Valverde, Francisco
Instituto Tecnologico de Informatica
Palau, Carlos E.
Universitat Politècnica de València
Pellicer, Andreu Belsa
Universitat Politècnica de València
Gizelis, Christos A.
OTE S.A.
Krassas, Dimosthenes
OTE S.A.
Becha, Hanane
Traxens, France
Khouani, Réda
Traxens, France
Metzger, Andreas
Universität Duisburg-Essen
Tzagkarakis, Nikos
National Technical University of Athens (NTUA)
Karkoglou, Anthousa
National Technical University of Athens (NTUA)
Nikolakopoulos, Anastasios
National Technical University of Athens (NTUA)
Marinakis, Achilleas
National Technical University of Athens (NTUA)
Moulos, Vrettos
National Technical University of Athens (NTUA)
Litke, Antonios
National Technical University of Athens (NTUA)
Ahmadian, Amir Shayan
Universität Koblenz
Jürjens, Jan  
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Mainwork
Technologies and Applications for Big Data Value  
Open Access
DOI
10.1007/978-3-030-78307-5_20
Additional full text version
Landing Page
Language
English
Fraunhofer-Institut für Software- und Systemtechnik ISST  
Keyword(s)
  • Data for AI

  • Industry 4.0

  • Port authorities

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