Digital twin architectures for smart port operations: Lessons from European benchmarking

Read full text
Authors: Raquel Gil-Pereira, Rui Borges Lopes, Leonor Teixeira
Cited by: 1
References: 89

Abstract

Digital Twins (DTs) are increasingly positioned as foundational technologies for improving operations in logistics and port ecosystems. This study aims to clarify how large European initiatives are currently designing and deploying DT technologies and to derive principles applicable to Smart Gate systems. A structured benchmarking analysis was conducted on publicly available documentation from funded projects available on the CORDIS platform. Seven initiatives that explicitly design or operationalize DTs across ports, multimodal logistics, smart mobility, and environmental-resilience systems were examined. The projects were analyzed in terms of their objectives, architectural design, data ecosystems, technological stacks, and modelling approaches. The results reveal converging trends, including decision-centric DTs, the centrality of interoperability, the need to integrate heterogeneous data sources, and the adoption of modular and service-oriented architectures. At the same time, the benchmarking highlights persistent gaps related to data availability, model transparency, and the reporting of operational performance, as well as limited detail on synchronization mechanisms. The study makes the following main contributions: (i) a structured benchmarking of seven European DT projects operating in logistics, mobility and port ecosystems; (ii) an integrated synthesis of recurring architectural, data, and modelling principles that underpin current DT implementations; and (iii) a proposed layered reference framework for a context-aware Smart Gate DT, together with key design principles related to interoperability, data integration, modelling, and decision-support functions.

Fields of Study & Subjects

Maritime Ports and Logistics Digital Transformation in Industry Maritime Transport Emissions and Efficiency

Publication details

Journal / source
Results in Engineering
Publisher
Elsevier BV
Volume
30
Pages
110485–110485
Publication date
9 April 2026
Language
EN