Search Results (75)

The large-scale integration of renewable energy and electric vehicles(EVs) into power distribution systems presents complex operational challenges, particularly in coordinating market mechanisms with grid stability requirements. This study proposes a new dispatching method based on dynamic electricity prices to coordinate the relationship between the market and the physical characteristics of the power grid. The proposed approach introduces a multi-agent transaction model incorporating voltage regulation metrics and network loss considerations into market bidding mechanisms. For EV integration, a differentiated scheduling strategy categorizes vehicles based on usage patterns and charging elasticity. The methodological innovations primarily include an enhanced scheduling algorithm for coordinated optimization of renewable energy and energy storage, and a dynamic coordinated optimization method for EV clusters. Implemented on a modified IEEE test system, the framework demonstrates improved voltage stability through price-guided energy storage dispatch, with coordinated strategies effectively balancing peak demand management and renewable energy utilization. Case studies verify the system’s capability to align economic incentives with technical objectives, where time-of-use pricing dynamically regulates storage operations to enhance reactive power support during critical periods. This research establishes a theoretical linkage between electricity market dynamics and grid security constraints, providing system operators with a holistic tool for managing high-renewable penetration networks. By bridging market participation with operational resilience, this work contributes actionable insights for developing interoperable electricity market architectures in energy transition scenarios. Full article

Sarcomas, a rare and complex group of cancers, require multidisciplinary care across multiple healthcare settings, often leading to delays, redundant testing, and fragmented data. This fragmented care landscape obstructs the implementation of Value-Based Healthcare (VBHC), where care efficiency is tied to measurable patient outcomes.ShapeHub, an interoperable digital platform, aims to streamline sarcoma care by centralizing patient data across providers, akin to a logistics system tracking an item through each stage of delivery. ShapeHub integrates diagnostics, treatment records, and specialist consultations into a unified dataset accessible to all care providers, enabling timely decision-making and reducing diagnostic delays. In a case study within the Swiss Sarcoma Network, ShapeHub has shown substantial impact, improving diagnostic pathways, reducing unplanned surgeries, and optimizing radiotherapy protocols. Through AI-driven natural language processing, Fast Healthcare Interoperability Resources, and Health Information Exchanges, HIEs, the platform transforms unstructured records into real-time, actionable insights, enhancing multidisciplinary collaboration and clinical outcomes. By identifying redundancies, ShapeHub also contributes to cost efficiency, benchmarking treatment costs across institutions and optimizing care pathways. This data-driven approach creates a foundation for precision medicine applications, including digital twin technology, to predict treatment responses and personalize care plans. ShapeHub offers a scalable model for managing rare cancers and complex diseases, harmonizing care pathways, improving precision oncology, and transforming VBHC into a reality. This article outlines the potential of ShapeHub to overcome fragmented data barriers and improve patient-centered care. Full article

Traditional horticultural information systems lack fine-grained, transparent on-farm event traceability, often providing only high-level post-harvest summaries. These systems also fail to standardise and integrate diverse data sources, ensure data privacy, and scale effectively to meet the demands of modern agriculture. Concurrently, rising requirements for global environmental, social, and governance (ESG) compliance, notably Scope 3 emissions reporting, are driving the need for farm-level visibility. To address these gaps, this study proposes a novel traceability framework tailored to horticulture, leveraging global data standards. The system captures key on-farm events (e.g., irrigation, harvesting, and chemical applications) at varied resolutions, using decentralised identification, secure data-sharing protocols, and farmer-controlled access. Built on a progressive Web application with microservice-enabled cloud infrastructure, the platform integrates dynamic APIs and digital links to connect on-farm operations and external supply chains, resolving farm-level data bottlenecks. Initial testing on Victorian farms demonstrates its scalability potential. Pilot studies further validate its on-farm interoperability and support for sustainability claims through digitally verifiable credentials for an international horticultural export case study. The system also provides a tested baseline for integrating data to and from emerging technologies, such as farm robotics and digital twins, with potential for broader application across agricultural commodities. Full article

In recent years, innovative Non-Destructive Testing (NDT) techniques, applicable for the assessment of existing civil structures, have become available for in situ analysis on Reinforced Concrete (RC) and masonry structures, but they are still not established for regular inspections, especially after seismic events. The damage assessment of RC buildings after seismic events is a very relevant issue in Italy, where most of the structures built in the last 50 years are RC structures. Furthermore, there is also a growing interest in being able to monitor structural health aspects by storing them on the building’s digital twin. For these reasons, it is necessary to develop an affordable and ready-to-use NDT procedure that provides more accurate indications on the real state of damage of reinforced concrete buildings after seismic events and to integrate these data into an interoperable digital twin for automated, optimized building performance monitoring, management, and preventive maintenance. To this end, a case study was conducted on a building in the Marche region in Italy, damaged by the 2016 earthquake. Non-destructive tests were performed and inserted into the LIS platform for the creation of a digital twin of the building. This platform seamlessly manages, visualizes, and analyzes the collected data and integrates various sensor nodes deployed throughout the building. The paper also presents a methodology to simplify the work of the test operator and make the entire process of knowledge of the building faster and more sustainable through a QR-code interface. Full article

In the realm of sustainable construction, Life Cycle Assessment (LCA) plays a key role as a tool for quantifying the environmental impacts of building materials and products. The integration of LCA and Building Information Modeling (BIM) makes it possible to evaluate the environmental performance of buildings at the design stage. This integration can help to improve the LCA process for buildings thanks to the potential for automation and interoperability. The goal of this study is to establish a BIM-based LCA workflow using the Industry Foundation Classes (IFC) open file format. The interoperability of BIM data exchange is achieved by applying IFC. The steps of the assessment process are described in accordance with the LCA phases outlined in the ISO 14040 standard. The impact assessment and results interpretation phases are automated by means of a program code for IFC file processing. The proposed BIM-based LCA is validated for a case study of a BIM model constructed for a three-story educational building. The GWP of the building materials and products of envelope and load-bearing structures at the A1–A3 life cycle stages are calculated for the purpose of proposed workflow testing. The resulting workflow allows for the calculation of negative environmental impacts to be agile, depending on the goal and scope set. Full article

Modern manufacturing systems are influenced by the growing complexity of mechatronics, control systems, IIoT, and communication technologies integrated into cyber-physical systems. These systems demand flexibility, modularity, and rapid project execution, making digital tools critical for their design. Virtual commissioning, based on digital twins, enables the testing and validation of control systems and designs in virtual environments, reducing risks and accelerating time-to-market. This research explores the development of digital twin models to bridge the gap between simulation and real-world validation. The models identify design flaws, validate the PLC control code, and ensure interoperability across software platforms. A case study involving a modular Festo manufacturing system modelled in Tecnomatix Process Simulate demonstrates the ability of digital twins to detect inefficiencies, such as collision risks, and to validate automation systems virtually. This study highlights the advantages of virtual commissioning for optimizing manufacturing systems. Communication testing showed compatibility across platforms but revealed limitations with certain data types due to software constraints. This research provides practical insights into creating robust digital twin models, improving the flexibility, efficiency, and quality of manufacturing system design. It also offers recommendations to address current challenges in interoperability and system performance. Full article

The evolution of cellular networks from fifth-generation (5G) architectures to beyond 5G (B5G) and sixth-generation (6G) systems necessitates innovative solutions to overcome the limitations of traditional Radio Access Network (RAN) infrastructures. Existing monolithic and proprietary RAN components restrict adaptability, interoperability, and optimal resource utilization, posing challenges in meeting the stringent requirements of next-generation applications. The Open Radio Access Network (O-RAN) and Multi-Access Edge Computing (MEC) have emerged as transformative paradigms, enabling disaggregation, virtualization, and real-time adaptability—which are key to achieving ultra-low latency, enhanced bandwidth efficiency, and intelligent resource management in future cellular systems. This paper presents a Federated Deep Reinforcement Learning (FDRL) framework for dynamic radio and edge computing resource allocation and slicing management in O-RAN environments. An Integer Linear Programming (ILP) model has also been developed, resulting in the proposed FDRL solution drastically reducing the system response time. On the other hand, unlike centralized Reinforcement Learning (RL) approaches, the proposed FDRL solution leverages Federated Learning (FL) to optimize performance while preserving data privacy and reducing communication overhead. Comparative evaluations against centralized models demonstrate that the federated approach improves learning efficiency and reduces bandwidth consumption. The system has been rigorously tested across multiple scenarios, including multi-client O-RAN environments and loss-of-synchronization conditions, confirming its resilience in distributed deployments. Additionally, a case study simulating realistic traffic profiles validates the proposed framework’s ability to dynamically manage radio and computational resources, ensuring efficient and adaptive O-RAN slicing for diverse and high-mobility scenarios. Full article

The International Maritime Organization (IMO) introduced the Maritime Service Portfolio (MSP) and Maritime Single Window (MSW) to enhance the digitalization and efficiency of maritime transportation. While the MSP defines 16 maritime services focused on safety, security, efficiency, and environmental protection, the MSW provides a unified digital platform for submitting and processing information related to a ship’s operations. To support the implementation of MSW, the IMO Compendium provides standardized data sets and reference models to enable seamless information exchange across maritime systems. This paper proposes an expansion of the IMO Compendium to integrate the MSP’s maritime safety information service into the MSW environment. The study focuses on the integration of NAVTEX messages, a key source of navigational safety information, by identifying their key attributes and structuring them according to the IHO S-124 standard. A case study demonstrates the feasibility of the proposed data structure by transforming a sample NAVTEX message into the expanded IMO Compendium format and testing its transmission using an open-source MQTT library. This paper provides a structured methodology for integrating NAVTEX messages, effectively bridging legacy systems with modern digital infrastructures and facilitating enhanced interoperability in maritime operations. The proposed data structure will be presented to standardization bodies for further consideration, contributing to ongoing efforts to improve maritime operational efficiency and support digital transformation. Full article

Advanced vehicle technologies that substitute or assist the driver are crucial and safety-critical elements, including independently acting electronic control units. A key element of vehicle road safety is its behavior on the road, influenced by various factors such as adhesion and physical forces. Self-activating brake systems, including related sensors and processing units, are vital for modern autonomous vehicles. The complexity of software in vehicle electronic control units (ECUs) has significantly increased, making traditional testing methods inadequate. This paper explores the use of Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) testing methods in an automated test environment to enhance software development and testing processes. It can be demonstrated that there is interoperability between the HIL and SIL systems using the same test case implementation in the Vector CANoe simulation environment. As a result, it can be demonstrated that in the case of a safety-critical function, such as an ABS (anti-lock brake system) control intervention, the ECU control software behaves the same in both the HIL and SIL simulation environments. Full article

Background: The COVID-19 pandemic has necessitated changes in European healthcare systems, with a significant proportion of COVID-19 cases being managed on an outpatient basis in primary healthcare (PHC). To alleviate the burden on healthcare facilities, many European countries developed contact-tracing apps and symptom checkers to identify potential cases. As the pandemic evolved, the European Union introduced the Digital COVID-19 Certificate for travel, which relies on vaccination, recent recovery, or negative test results. However, the integration between these apps and PHC has not been thoroughly explored in Europe. Objective: To describe if governmental COVID-19 apps allowed COVID-19 patients to connect with PHC through their apps in Europe and to examine how the Digital COVID-19 Certificate was obtained. Methodology: Design and setting: Retrospective descriptive study in PHC in 30 European countries. An ad hoc, semi-structured questionnaire was developed to collect country-specific data on primary healthcare activity during the COVID-19 pandemic and the use of information technology tools to support medical care from 15 March 2020 to 31 August 2021. Key informants belong to the WONCA Europe network (World Organization of Family Doctors). The data were collected from relevant and reliable official sources, such as governmental websites and guidelines. Main outcome measures: Patient’s first contact with health system, governmental COVID-19 app (name and function), Digital COVID-19 Certification, COVID-19 app connection with PHC. Results: Primary care was the first point of care for suspected COVID-19 patients in 28 countries, and 24 countries developed apps to complement classical medical care. The most frequently developed app was for tracing COVID-19 cases (24 countries), followed by the Digital COVID-19 Certificate app (17 countries). Bulgaria, Italy, Serbia, North Macedonia, and Romania had interoperability between PHC and COVID-19 apps, and Poland and Romania’s apps considered social needs. Conclusions: COVID-19 apps were widely created during the first pandemic year. Contact tracing was the most frequent function found in the registered apps. Connection with PHC was scarcely developed. In future pandemics, connections between health system levels should be guaranteed to develop and implement effective strategies for managing diseases. Full article

The prosperity of Po River Valley’s quality agri-food system depends on the efficiency of its field crops, which are recently facing a crisis evidenced by cultivated areas decreasing and yields stagnating. Several factors, including EU policies and climate variability, impose an improvement in the use of production factors and adapted business models: literature shows how digitalization and Agriculture 4.0 can contribute to addressing these challenges. This paper aims to explore drivers and barriers in the adoption of digitalization among Po River Valley field crop farms, in a dynamic view. Using a case study approach to guarantee adequate consideration of context and conditions, three farms were studied. As one of the main outcomes, several drivers (digital skills, data management practices, and interoperability) that should be at the heart of policies were identified as demands to farmers in exchange for financial contributions, or as “innovation space” offered by EU institutions. Policies should not only focus on supporting mechanical/digital equipment acquisition but also on promoting the evolution of farmers’ human capital. The framework developed paves the way for future research on the degree of farm digitalization in the same/similar territorial contexts: identified drivers of digital transition can be used as a basis for survey questionnaires, as well as tested in their validity. Full article

Over the years, RDF streaming has been explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge in discussing and integrating streaming systems due to a lack of a common language. This work attempts to address this critical research gap by systematizing RDF stream types present in the literature in a novel taxonomy. The proposed RDF Stream Taxonomy (RDF-STaX) is embodied in an OWL 2 DL ontology that follows the FAIR principles, making it readily applicable in practice. Extensive documentation and additional resources are provided to foster the adoption of the ontology. Three use cases for the ontology are presented with accompanying competency questions, demonstrating the usefulness of the resource. Additionally, this work introduces a novel nanopublications dataset, which serves as a collaborative, living state-of-the-art review of RDF streaming. The results of a multifaceted evaluation of the resource are presented, testing its logical validity, use case coverage, and adherence to the community’s best practices, while also comparing it to other works. RDF-STaX is expected to help drive innovation in RDF streaming by fostering scientific discussion, cooperation, and tool interoperability. Full article

This paper proposes a new approach to the design of smart charging systems. It aims to separate the role of the Smart Charging Service Provider (SCSP) from the role of the Charge Point Operator (CPO) to provide real flexibility and efficiency of mass deployment. As interoperability is required for this purpose, the challenge is to use standard equipment and protocols in the design of the smart charging Energy Management System (EMS). The use of an Open Charge Point Interface (OCPI) is crucial for an interface between the EMS and the Charge Point Operator. The smart charging EMS developed has been implemented and successfully tested with two CPOs, with different use cases: (1) EV charging infrastructure at office buildings, and (2) EV charging infrastructure installed at a public car park facility. Full article

Data integration is considered a classic research field and a pressing need within the information science community. Ontologies play a critical role in such processes by providing well-consolidated support to link and semantically integrate datasets via interoperability. This paper approaches data integration from an application perspective by looking at ontology matching techniques. As the manual matching of different sources of information becomes unrealistic once the system scales up, the automation of the matching process becomes a compelling need. Therefore, we have conducted experiments on actual non-semantically enriched relational data with the support of existing tools (pre-LLM technology) for automatic ontology matching from the scientific community. Even considering a relatively simple case study—i.e., the spatio–temporal alignment of macro indicators—outcomes clearly show significant uncertainty resulting from errors and inaccuracies along the automated matching process. More concretely, this paper aims to test on real-world data a bottom-up knowledge-building approach, discuss the lessons learned from the experimental results of the case study, and draw conclusions about uncertainty and uncertainty management in an automated ontology matching process. While the most common evaluation metrics clearly demonstrate the unreliability of fully automated matching solutions, properly designed semi-supervised approaches seem to be mature for more generalized application. Full article

The conect4children (c4c) initiative was established to facilitate the development of new drugs and other therapies for paediatric patients. It is widely recognised that there are not enough medicines tested for all relevant ages of the paediatric population. To overcome this, it is imperative that clinical data from different sources are interoperable and can be pooled for larger post hoc studies. c4c has collaborated with the Clinical Data Interchange Standards Consortium (CDISC) to develop cross-cutting data resources that build on existing CDISC standards in an effort to standardise paediatric data. The natural next step was an extension to disease-specific data items. c4c brought together several existing initiatives and resources relevant to disease-specific data and analysed their use for standardising disease-specific data in clinical trials. Several case studies that combined disease-specific data from multiple trials have demonstrated the need for disease-specific data standardisation. We identified three relevant initiatives. These include European Reference Networks, European Joint Programme on Rare Diseases, and Pistoia Alliance. Other resources reviewed were National Cancer Institute Enterprise Vocabulary Services, CDISC standards, pharmaceutical company-specific data dictionaries, Human Phenotype Ontology, Phenopackets, Unified Registry for Inherited Metabolic Disorders, Orphacodes, Rare Disease Cures Accelerator-Data and Analytics Platform (RDCA-DAP), and Observational Medical Outcomes Partnership. The collaborative partners associated with these resources were also reviewed briefly. A plan of action focussed on collaboration was generated for standardising disease-specific paediatric clinical trial data. A paediatric data standards multistakeholder and multi-project user group was established to guide the remaining actions—FAIRification of metadata, a Phenopackets pilot with RDCA-DAP, applying Orphacodes to case report forms of clinical trials, introducing CDISC standards into European Reference Networks, testing of the CDISC Pediatric User Guide using data from the mentioned resources and organisation of further workshops and educational materials. Full article