H2TRAIN aligns with the ECS Strategic Research and Innovation Agenda 2023 (ECS-SRIA), addressing key challenges in integrating digital technologies for health-focused lifestyles through AI-enhanced networks. This project pioneers the use of graphene to develop autonomous biosensors within CMOS technology, supporting advancements in AI-powered health services and IoT applications. Beyond digital integration, H2TRAIN innovates in energy detection, collection, and storage, essential for embedding health and sports functions in IoT wearables through smart textile and system integration. The solutions will be rigorously tested and validated with insights from medical, sports, social sciences, and end-user feedback. Focused on remote assisted living, amateur sports training, and post-operative monitoring, H2TRAIN aims to drive innovation in the smart healthcare sector, where investment in semiconductor nanofabrication is limited by the small scale of medical applications.

The FEDERATE and HAL4SDV projects aim to address the growing importance of software in the automotive industry, positioning Europe as a leader in the software-defined vehicle (SDV) domain. FEDERATE focuses on building a cohesive European SDV ecosystem by coordinating stakeholders such as OEMs, tiers, semiconductor companies, and research institutions. It supports the agile development of a non-differentiating automotive software platform through open-source collaboration, fostering a vibrant SDV community and providing guidance for ongoing and future SDV projects. Meanwhile, HAL4SDV aligns with the ECS Strategic Research and Innovation Agenda to develop technologies and processes needed for SDV advancement beyond 2030. HAL4SDV's objectives include creating a unified software interface, hardware abstraction, and Over-The-Air updates, while focusing on cybersecurity, real-time capabilities, and seamless integration of new software functions and modified software building blocks into the target vehicle system. Together, these projects aim to drive innovation, scalability, and sustainability in the SDV area.

Nowadays, the need to efficiently process information in Internet of Things (IoT)-oriented heterogeneous scenarios has increased significantly, e.g., in all scenarios where unobtrusive environmental monitoring is beneficial for the involved people (e.g., inside public transport vehicles, indoor workplaces and offices, large public infrastructures, etc.). This objective typically requires the combination of heterogeneous IoT systems, which need to efficiently share information, e.g., through the Web of Things (WoT) paradigm. In this paper, we propose an edge computing-oriented flexible WoT architecture, with distributed intelligence, for air quality monitoring and prediction inside a public transport bus. Our results show that the proposed architecture allows seamless integration of heterogeneous IoT systems according to a WoT perspective, exploiting the device/edge/fog computing continuum and using containerized and secure processing modules.

Eclipse Arrowhead is an open and flexible framework for industrial IoT scenarios based on service-oriented principles. It allows building highly configurable Systems of Systems by connecting systems running on devices in a local cloud. Part of Arrowhead’s flexibility is its ability to integrate other systems and tools through core services. In a previous study, we identified projects from Eclipse IoT, one of the largest open source communities for Internet of Things (IoT), building production-ready systems and tools for IoT. Based on this study, we integrated suitable projects into the Eclipse Arrowhead Framework, validating our initial findings and providing integrations complementing Arrowhead’s core functionality. The paper summarizes the integrations and gives an outlook on the next steps.

The Internet of Things (IoT), and more specifically the industrial IoT, is revolutionising industry. This technology has catalyzed the fourth industrial revolution and inspired movements such as Industry 4.0, the Industrial Internet Consortium and Society 5.0. Morphing an industrial process or assembly line to aggregate Internet-connected devices and systems does not complete the picture. The concept penetrates all aspects of the engineering process (EP) which encompasses the full life-cycle of the product/solution. Phases of the EP traditionally tended to be sequential but, with the IoT, can now evolve and influence other phases throughout the product/solution life-cycle. The EU-funded Arrowhead Tools project aims to promote a service-oriented architecture (SOA) to allow tools within each phase of the engineering process to interact with each other. This paper, applies the proposed EP model to a real value chain composed of multiple stakeholders adopting different EPs for the life-cycle management of a Smart Boiler System.

The Internet Of Things (IoT) is an emerging paradigm that envisions a networked infrastructure enabling different types of devices to be interconnected. It creates different kinds of artifacts (e.g., services and applications) in various application domains such as health monitoring, sports monitoring, animal monitoring, enhanced retail services, and smart homes. Recommendation technologies can help to more easily identify relevant artifacts and thus will become one of the key technologies in future IoT solutions. In this article, we provide an overview of existing applications of recommendation technologies in the IoT context and present new recommendation techniques on the basis of real-world IoT scenarios.

Semantic Web technologies act as an interoperability glue among different formats, protocols and platforms, providing a uniform vision of heterogeneous devices and services in the Internet of Things (IoT). Semantic Web technologies can be applied to a broad range of application contexts (i.e., industrial automation, automotive, health care, defense, finance, smart cities) involving heterogeneous actors (i.e., end users, communities, public authorities, enterprises). Smart-M3 is a semantic publish-subscribe software architecture conceived to merge the Semantic Web and the IoT domains. It is based on a core component (SIB, Semantic Information Broker) where data is stored as RDF graphs, and software agents using SPARQL to update, retrieve and subscribe to changes in the data store. This article describes a OSGi SIB implementation extended with a new persistent SPARQL update primitive. The OSGi SIB performance has been evaluated and compared with the reference C implementation. Eventually, a first porting on Android is presented.

The increasing processing power of today's HW/SW platforms leads to the integration of more and more functions in a single device. Additional design challenges arise when these functions share computing resources and belong to different criticality levels. The paper presents the CONTREX European project and its preliminary results. CONTREX complements current activities in the area of predictable computing platforms and segregation mechanisms with techniques to consider the extra-functional properties, i.e., timing constraints, power, and temperature. CONTREX enables energy efficient and cost aware design through analysis and optimization of these properties with regard to application demands at different criticality levels.

The study and engineering of Electro Mobility (EM) involves many industrial and academic players due to its potential significant benefits on society, economy, transportation and eco-sustainability. This article proposes a solution for EM automation, a crucial aspect for the future evolution of the EM market. The solution is based on a service-oriented, IoT and cloud centric ecosystem of charging stations conceived to support EM scenarios. The Eclipse Kura framework ensures the information exchange between the charging stations and the cloud infrastructure, providing remote management and data processing. The cloud platform is based on Eurotech EC and provides an internal service abstraction that offers efficient and secure mechanisms to collect raw data from the field. Kura is used to process data and store them on the cloud as semantically referenced information. Cloud services are accessible through a simple REST interface and published on the Arrowhead Framework, which is responsible for the integration of the multi-domain EM scenario. A real use case about the automation of a rural fast charging infrastructure is described and the benefits of applying the proposed solution to the use case are discussed with the help of the simulation results.

The design of applications that may benefit from the data gathered from the surrounding physical environment represents a challenging and promising research field. Because of the heterogeneity of such systems interoperability is becoming more difficult to achieve at the service, information and device levels. In this paper, we report on the first attempt to design an interoperability platform by integrating a “Semantic Web” information sharing infrastructure, namely Smart-M3 (Multi-part, Multi-device and Multi-vendor), within the OSGi (Open Service Gateway initiative) framework, enhancing the information level interoperability of the former with the service level interoperability of the latter. Such an interoperability platform can grant the unanticipated evolution of existing Information and Communication Technology (ICT) systems by providing a generic and simple solution to develop what are generally called “Smart Space Applications”. As proof of concept a maintenance scenario will be discussed and detailed.

We propose a novel energy-efficient cache architecture based on a matching mechanism that uses a reduced number of tag bits. The idea behind the proposed architecture is based on moving a large subset of the tag bits from the cache into an external register (called theTagOverflowBuffer) that serves as an identifier of the current locality of the memory references. Dynamic energy efficiency is achieved by accessing, for most of the memory references, a reduced-tag cache; furthermore, because of the reduced number of tag bits, leakage energy is also reduced as a by-product. We achieve average energy savings ranging from 16% to 40% (depending on different cache structural parameters) on total (i.e., static and dynamic) cache energy, and measured on a standard suite of embedded applications.

We propose a novel energy-efficient memory architecture which relies on the use of a cache with a reduced number of tag bits. The idea behind the proposed architecture is based on moving a large number of the tag bits from the cache into an external register (tag overflow buffer) that identifies the current locality of the memory references; additional hardware allows us to dynamically update the value of the reference locality contained in the buffer. Energy efficiency is achieved by using, for most of the memory accesses, a reduced-tag cache. This architecture is minimally intrusive for existing designs, since it assumes the use of a regular cache, and does not require any special circuitry internal to the cache such as row or column activation mechanisms. Average energy savings are 51% on tag energy, corresponding to about 20% saving on total cache energy, measured on a set of typical embedded applications.

Many approaches have been proposed for digital system verification, either based on simulation strategies or on formal verification techniques. Both of them show advantages and drawbacks and new mixed approaches have been presented in order to improve the verification process. Specifically, the adoption of formal methods still lacks a coverage metrics to let the verification engineer get a measure of which portion of the circuit is already covered by the written properties that far and which parts still need to be addressed. The present paper describes a new simulation based methodology aimed at measuring the error coverage achieved by temporal assertions proved by model checking. The approach has been applied to the description of a protocol converter block, and some preliminary results are presented in the paper.