Digital Twins are software technologies that enable the modelling of real-world phenomena in digitised environments, representing and monitoring the reality of various processes, including IoT deployments. Since 2017, the use of Digital Twins has been increasing. However, in the road transport and logistics realm, the adoption rate remains low, primarily due to the costs of processing and validating data in centralised scenarios, among other factors. On the other hand, Blockchain technologies were created to provide immutable and decentralised data storage in diverse scenarios, adding a layer of isolation and reliability in heterogeneous solutions. This paper presents a case study proposing a Digital Twin based on open-source Blockchain technologies, such as FIWARE Canis Major. The primary goal is to design and implement a robust and efficient open-source architecture that allows for the control and optimisation of vehicle fleet allocations in logistics/transport companies within supply chain management. This case study aims to showcase the practical application of the proposed solution in a real-world context, providing insights into its eco-friendly and low-cost attributes while opening the door to a large number of additional applications.

Data-driven industrial value networks increasingly rely on creating and maintaining data value ecosystems, complete with trusted sharing and effective distributed data processing. However, challenges arise due to diverse use cases, large data volumes, data value and quality maintenance, and data source heterogeneity. To enhance data sharing, initiatives like International Data Spaces (IDS) propose enablers for trusted data sharing, allowing data owners to determine sovereignty basis. This chapter addresses the main challenges related to the evolution of sovereign Data Spaces in three critical dimensions: (1) improving their data reuse and exchangeability; (2) defining common models to increase data interoperability: and (3) ensure high data quality. For these reasons, this approach goes beyond the traditional Data Space technologies to propose "Data as a Product" (DaaP) as the core enabling concept to facilitate the implementation of digital continuity across Data Spaces, AI/ML/Data pipelines, Digital Twins workflows and digital threads. This chapter will provide an overview of the state of the art on strategies for Digital 4.0 Continuum. Finally, the Horizon Europe RE4DY project as a DaaP use case will be introduced.

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.

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.

As Internet of Things networks grow in heterogeneity and complexity, the associated industry needs to improve the performance of traditional network deployments. One of the main relevant evolutions on network architectures is depicted by the remote control of the forwarding state of the equipment. The advance here consists in having the data plane managed by a remotely controlled plane decoupled from the former, enabling to program the behavior of a network without being tied to inflexible rules and conditions. To support this network evolution, software-defined networking (SDN) allows programmability as the main role in improving resource efficiency and increasing service reliability and security. The analysis conducted in this paper aims at reviewing the different adoption strategies to effectively deploy SDN-enabled Next Generation IoT systems, analyzing in detail the variations found between the types of access network layers, and the SDN applications that can be carried out. The analysis ranges from basic deployments (where the concerns are specific to the direct connection end devices-network) to complex, multi-application advanced ones (where alternative configuration and layouts come into play). The paper concludes with the presentation of the approach taken in the project ASSIST-IoT, that will apply the previous knowledge toward the definition of a blueprint architecture for the Next Generation Internet of Things.

This paper aims at devising an IoT-based system to collaboratively calculate quantitative composite indicators among Industrial actors. Requirements have been considered to build a reliable, trusted, anonymised environment within which involved stakeholders can safely share information on the indicators while keeping sovereignty over their data. Technologies such as enhanced Context Brokers, the usage of Industrial Data Spaces agents and the introduction of distributed publish-subscribe data exchange schemes lay the foundations of the proposed solution. This work entails the design of the system altogether with a proposal of technologies for its deployment. Drawing from previous public-funded projects' results and highly relying on open-source technologies, the authors have come up with a solution that aims to be proven in real environments in the near future.

The average life expectancy of the world’s population is increasing and the healthcare systems sooner than later will be compromised by its reduced capacity and its highly economic cost; in addition, the age distribution of the population is leading towards the older spectrum. This trend will lead to immeasurable and unexpected economic problems and social changes. In order to face up this challenge and complex economic and social problem, it is necessary to rely on the appropriate digital tools and technological infrastructures for ensuring that the elderly are properly cared in their everyday living environments and they can live independently for longer. This article presents ACTIVAGE IoT Ecosystem Suite (AIoTES), a concrete reference architecture and its implementation process that addresses these issues and that was designed within the first European Large Scale Pilot, ACTIVAGE, a H2020 funded project by the European Commission with the objective of creating sustainable ecosystems for Active and Healthy Ageing (AHA) based on Internet of Things and big data technologies. AIoTES offers platform level semantic interoperability, with security and privacy, as well as Big Data and Ecosystem tools. AIoTES enables and promotes the creation, exchange and adoption of cross-platform services and applications for AHA. The number of existing AHA services and solutions are quite large, especially when state-of-the-art technology is introduced, however a concrete architecture such as AIoTES gains more importance and relevance by providing a vision for establishing a complete ecosystem, that looks for supporting a larger variety of AHA services, rather than claiming to be a unique solution for all the AHA domain problems. AIoTES has been successfully validated by testing all of its components, individually, integrated, and in real-world environments with 4345 direct users. Each validation is contextualized in 11 Deployment Sites (DS) with 13 Validation Scenarios covering the heterogeneity of the AHA-IoT needs. These results also show a clear path for improvement, as well as the importance for standardization efforts in the ever-evolving AHA-IoT domain.

A interoperability layer is fundamental to provide a global continuum interoperability among IoT platforms. To address this layer, the following activities have been carried out: (i) design of device-to-device interaction based on multiprotocol/access mechanisms; (ii) design of software defined interoperable modules for mobility and routing; (iii) development of an open management framework for smart objects; (iv) design and implementation of smart IoT application service gateway and virtualization; and (v) definition of a common ontology which will facilitate access to the heterogeneous data, data that will be collected and managed by integrated IoT platforms.

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.

Applications and Services are located at the top of the IoT deployments and represent a big portion of the IoT stack. Each Platform has several IoT Services and these use to be domain-oriented and very heterogeneous. This heterogeneity hinders the interoperability between services and applications from different IoT Platforms. Flow Based Programming is a paradigm that allows the interconnection of services and the creation of an execution flow between them. There are several solutions that use this paradigm within the IoT platforms, but none is mainly focused in the aim of connect services from different IoT platforms. To address this, a methodology is described to develop functionalities to access to the services, and an architecture is provided with different components to offer a solution to this interoperability problem. This solution offers advantages in the registry, cataloging and discovery of services, and in the creation and management of composite IoT Services. Finally, this paper show a use case related with transport and logistic to validate this approach.

Chronic Obstructive Pulmonary Disease (COPD) is a wide concept to describe a group of diseases which affect a normal respiratory function and cause a considerable impact on patients' life quality and healthcare costs. There are few IoT systems in the present literature that are focused on monitoring and management of COPD patients, but they are not focused on the vast amount of data that IoT generates in a large scale deployment, and the integration of Smart City services. For these reasons, this paper presents an innovative system based on Cloud Computing and Big Data technologies to integrate Smart City services into a large scale scenario. To do so, this system proposes a Big Data architecture based on Apache Spark libraries to provide data integration, storage, descriptive and predictive analysis. Also, the system provides a web interface application where users can visualize the data analysis results. They show that the data enrichment function performed on the Big Data architecture provides more information about the environment to improve decisionmaking. This way, the system helps COPD patients to get more involved into decision making process and promote an active and healthy life by recommending the least polluted area to performance their daily activities.