During the past few decades, the combination of flourishing maritime commerce and urban population increases has made port-cities face several challenges. Smart Port-Cities of the future will take advantage of the newest IoT technologies to tackle those challenges in a joint fashion from both the city and port side. A specific matter of interest in this work is how to obtain reliable, measurable indicators to establish port-city policies for mutual benefit. This paper proposes an IoT-based software framework, accompanied with a methodology for defining, calculating, and predicting composite indicators that represent real-world phenomena in the context of a Smart Port-City. This paper envisions, develops, and deploys the framework on a real use-case as a practice experiment. The experiment consists of deploying a composite index for monitoring traffic congestion at the port-city interface in Thessaloniki (Greece). Results were aligned with the expectations, validated through nine scenarios, concluding with delivery of a useful tool for interested actors at Smart Port-Cities to work over and build policies upon.

Over the last few years, the European Union (EU) has placed significant emphasis on the interoperability of critical infrastructures (CIs). One of the main CI transportation infrastructures are ports. The control systems managing such infrastructures are constantly evolving and handle diverse sets of people, data, and processes. Additionally, interdependencies among different infrastructures can lead to discrepancies in data models that propagate and intensify across interconnected systems. This article introduces “BigDaM”, a Big Data Management framework for critical infrastructures. It is a cutting-edge data model that adheres to the latest technological standards and aims to consolidate APIs and services within highly complex CI infrastructures. Our approach takes a bottom-up perspective, treating each service interconnection as an autonomous entity that must align with the proposed common vocabulary and data model. By injecting strict guidelines into the service/component development’s lifecycle, we explicitly promote interoperability among the services within critical infrastructure ecosystems. This approach facilitates the exchange and reuse of data from a shared repository among developers, small and medium-sized enterprises (SMEs), and large vendors. Business challenges have also been taken into account, in order to link the generated data assets of CIs with the business world. The complete framework has been tested in the main EU ports, part of the transportation sector of CIs. Performance evaluation and the aforementioned testing is also being analyzed, highlighting the capabilities of the proposed approach.

The increasing exchange of goods by sea is contributing significantly to pollution in port areas. Although several methods have been developed to assess the environmental performance of ports, most of them have shortcomings including a qualitative-only approach and self-assessment of environmental performance. Therefore, there is a pressing need to develop a different approach based on quantitative measurements obtained through measurements at ports. In this paper we present the Port Environmental Index (PEI), a quantitative composite index of port environmental performance driven by IoT. The index allows for environmental measurements to be collected in real time or close to real time through sensors providing an assessment of a port’s environmental performance in real time. In addition, since the methodology for creating the index is standardised, the index makes it possible to compare different ports and rank them in terms of their environmental performance. As a proof of concept (PoC) this paper also describes the application of the index to the port of Thessaloniki (Greece).

Industrial automation is characterized by combining informational and operational technologies in an efficient manner to adapt to new production trends. Thus, mass customization often requires innovative approaches such as adopting computing continuum technologies. Here, relying on heterogeneous nodes from IoT to edge and cloud, the capabilities that these nodes can bring by themselves to better an ecosystem are crucial. A technological suite of those, accompanied by a relevant validation industrial scenario, is proposed in this work.