Interoperable Solutions Research Articles

Advancing Healthcare Through Interoperability: Implementing Scalable Solutions for Patient Data Integration.

Healthcare faces significant challenges in exchanging and utilizing health information across diverse providers, necessitating innovative solutions for improved interoperability. This study presents a comprehensive exploration of scalable technical and semantic solutions for patient care integration, emphasizing the implementation of these solutions within the framework of the Fast Healthcare Interoperability Resources (FHIR) standard. Our approach revolves around the development and deployment of Technical Interoperability Suite (TIS) and Semantic Interoperability Suite (SIS) technology solutions to disparate health information systems, predominantly Electronic Health Records (EHRs) into a unified Patient Care Platform, fostering comprehensive data exchange and utilization. The integration process involves importing data from various EHR systems and transforming imported patient data into FHIR-standardized formats. The provided solution supports various functionalities, including automatic and manual importation of patient data, through standard computer-readable templates. The integration of TIS and SIS solutions is underpinned by a robust technological framework, incorporating technologies such as Typescript, Deno, and document-oriented databases such as MongoDB. The effectiveness of our interoperability solutions was validated through deployment in multinational EU projects: ADLIFE and CAREPATH. The scalability and generalizability of our approach underscore its potential for diverse healthcare settings.

Formal Methods for Establishing Simulation Interoperability for Military Health System Applications.

Advancements in information technology have facilitated information exchange practices within the Military Health System (MHS), enabling "systems of systems" approaches that broaden and coordinate the set of capabilities available to enhance patient outcomes. This is applicable for MHS modeling and simulation (M&S) applications as well. Learning from successful approaches applied in current interoperability solutions used in the military helps to ensure interoperability practices yield trusted compositions of simulations. The use of formal methods provides the rigor necessary to unambiguously communicate these approaches across the MHS community. Here, 3 formal methods are proposed to ensure the harmonization of models and alignment of M&S data needed for simulation interoperability for MHS applications. To clarify considerations relevant for establishing simulation interoperability, the proposed formal methods are examined within a notional example of an injury sustained because of blast exposure. The first method applies the principles of semiotics, addressing the coding of information via syntax and semantics, to understand how to align and transform data across simulations within a composition. The second method applies the concepts of well-specified co-simulations, and the use of different techniques, tools, and algorithms to address the composition and synchronization of M&S components. The third method applies the mathematical branch of model theory to codify expert knowledge about concepts, assumptions, and constraints to ensure conceptual alignment within the simulation composition. Biomedical research must contend with complexity inherent to computational human body modeling, enlisting expert knowledge from multiple domains supporting the development of cross-disciplinary research tools that resolve research foci and associated differences in underlying theories, methods, and applied tools. This is closely related to the broader context of digital engineering for military systems engineering.

Musculoskeletal Disorder (MSD) Health Data Collection, Personalized Management and Exchange Using Fast Healthcare Interoperability Resources (FHIR).

With the proliferation and growing complexity of healthcare systems emerges the challenge of implementing scalable and interoperable solutions to seamlessly integrate heterogenous data from sources such as wearables, electronic health records, and patient reports that can provide a comprehensive and personalized view of the patient's health. Lack of standardization hinders the coordination between systems and stakeholders, impacting continuity of care and patient outcomes. Common musculoskeletal conditions affect people of all ages and can have a significant impact on quality of life. With physical activity and rehabilitation, these conditions can be mitigated, promoting recovery and preventing recurrence. Proper management of patient data allows for clinical decision support, facilitating personalized interventions and a patient-centered approach. Fast Healthcare Interoperability Resources (FHIR) is a widely adopted standard that defines healthcare concepts with the objective of easing information exchange and enabling interoperability throughout the healthcare sector, reducing implementation complexity without losing information integrity. This article explores the literature that reviews the contemporary role of FHIR, approaching its functioning, benefits, and challenges, and presents a methodology for structuring several types of health and wellbeing data, that can be routinely collected as observations and then encapsulated in FHIR resources, to ensure interoperability across systems. These were developed considering health industry standard guidelines, technological specifications, and using the experience gained from the implementation in various study cases, within European health-related research projects, to assess its effectiveness in the exchange of patient data in existing healthcare systems towards improving musculoskeletal disorders (MSDs).

The role of blockchain to secure internet of medical things

This study explores integrating blockchain technology into the Internet of Medical Things (IoMT) to address security and privacy challenges. Blockchain’s transparency, confidentiality, and decentralization offer significant potential benefits in the healthcare domain. The research examines various blockchain components, layers, and protocols, highlighting their role in IoMT. It also explores IoMT applications, security challenges, and methods for integrating blockchain to enhance security. Blockchain integration can be vital in securing and managing this data while preserving patient privacy. It also opens up new possibilities in healthcare, medical research, and data management. The results provide a practical approach to handling a large amount of data from IoMT devices. This strategy makes effective use of data resource fragmentation and encryption techniques. It is essential to have well-defined standards and norms, especially in the healthcare sector, where upholding safety and protecting the confidentiality of information are critical. These results illustrate that it is essential to follow standards like HIPAA, and blockchain technology can help ensure these criteria are met. Furthermore, the study explores the potential benefits of blockchain technology for enhancing inter-system communication in the healthcare industry while maintaining patient privacy protection. The results highlight the effectiveness of blockchain’s consistency and cryptographic techniques in combining identity management and healthcare data protection, protecting patient privacy and data integrity. Blockchain is an unchangeable distributed ledger system. In short, the paper provides important insights into how blockchain technology may transform the healthcare industry by effectively addressing significant challenges and generating legal, safe, and interoperable solutions. Researchers, doctors, and graduate students are the audience for our paper.

Considerations for trustworthy cross-border interoperability of digital identity systems in developing countries

AbstractIn developing nations, the implementation of Foundational Identity Systems (FIDS) has optimised service delivery and inclusive economic growth. Cross-border e-government will gain traction as developing countries increasingly look to identity federation and trustworthy interoperability through FIDS for the identification and authentication of identity holders. Despite this potential, the interoperability of FIDS in the African identity ecosystem has not been well-studied. Among the difficulties in this situation are the intricate internal political dynamics that have led to weak institutions, suggesting that FIDS could be used for political purposes; additionally, citizens’ or identity holders’ habitual low trust in the government raises concerns about data security and privacy protection. Similarly, vendor lock-in, cross-system compatibility, and ambiguous legislative rules for data exchange are other concerns. Interoperability is fundamentally necessary as a precondition for e-government services and serves as the foundation for the best possible service delivery in the areas of social security, education, and finance, as well as gender equality as demonstrated by the European Union (EU). Moreover, the integration of cross-border FIDS and an ecosystem of effective data governance will be created by unified data sharing via an interoperable identity system. Thus, in this study, we point to the challenges, opportunities, and requirements for cross-border interoperability in an African setting. Furthermore, we investigated current interoperability solutions such as the EU’s eIDAS and Estonian X-Road and proposed an approach for scoping requirements to achieve a fully functional interoperable identity ecosystem in the African setting. Our findings show that interoperability in the African identity ecosystem is essential for expanding the scope of e-government throughout the continent and for bolstering the smooth authentication and verification of identity holders for inclusive economic growth.

A unified component-based data-driven framework to support interoperability in the healthcare systems

Healthcare organizations must urgently prioritize interoperability to enhance the quality of care they provide. However, achieving this collaboration comes with numerous challenges, including differing approaches, data formats, and standards, as well as concerns about privacy, security, technical complexity, and legal and regulatory issues. To tackle these challenges, we determined a set of interoperability solutions. We also developed a comprehensive, component-based, data-driven framework for healthcare systems. Our study's approach involved three main steps: first, conducting a literature review to gather interoperability requirements and solutions from online databases and grey literature; second, carrying out a qualitative study to develop a framework based on the review results and focus group discussions; and third, using the Delphi method to validate the framework with experts. We extracted information from 36 articles during the screening and assessment process. Based on the proposed framework, we organized the identified themes into various categories, including architecture, architecture components, standards, platforms, policies, data sources, consumers, applications, level of interoperability, healthcare facilities, and considerations. Experts believe that establishing a comprehensive architecture for launching interoperability between health information systems can greatly facilitate this process. All framework components (totaling 197) received unanimous approval. The landscape of healthcare delivery is shifting from a focus on diseases to a patient-centered, data-driven approach. There is a growing demand for personalized healthcare systems, which necessitates increased interoperability among all healthcare stakeholders, particularly when dealing with diverse types of data. Our framework is designed to facilitate the implementation of various types of interoperability in healthcare systems.

Advancing IOT Interoperability: Dynamic Protocol Translation through Machine Learning For Enhanced Communication Efficiency

This study presents a pioneering methodology for Dynamic Protocol Translation in the Internet of Things (IoT), aiming to overcome challenges posed by diverse communication protocols among IoT devices. The primary objective is to develop a two-fold approach: first, acquiring data from IoT devices through their specific protocols, preprocessing it for consistency, and employing Natural Language Processing (NLP) techniques for semantic extraction and normalization; second, implementing a machine learning model, incorporating neural networks, to discern correlations between normalized representations and target protocol structures. The emphasis is on rigorous testing, validation, & real-time translation capabilities. The main conclusions of the study demonstrate how well the suggested Logistic Regression model performed, with an accuracy of 96.76%, in contrast to an existing model (XML-JSON) that had an accuracy of 82.41%. The detailed evaluation metrics, which include F1 score, precision, and recall, demonstrate how well the suggested method works to solve protocol translation issues. The iterative feedback loop, real-time translation, and secure data transfer of the proposed system improve its adaptability and reliability. This research enhances the field of IoT communication by offering a comprehensive solution for smooth interoperability & communication efficiency in a range of IoT applications.

Matter and ECHONET Lite: Similarities, differences, and a bridge solution for interoperability

With the increasing number of connected devices in smart homes, ensuring compatibility and interoperability is becoming increasingly more important. Matter and ECHONET Lite have been introduced to tackle this issue. While Matter is gaining significant attention globally as the future protocol for smart homes, ECHONET Lite has a long history of development and adoption in the smart home in Japan. Therefore, it is essential that both Matter and ECHONET Lite devices are interoperable to provide maximum benefits to users.In this paper, we provide an in-depth analysis that compares the architecture and features of Matter and ECHONET Lite, highlighting both their commonalities and differences. On top of that, we introduce a solution to bridge ECHONET Lite devices into the Matter ecosystem, enabling them to collaborate seamlessly with other Matter devices. This bridge solution is developed, implemented, and tested within a real smart home testbed installed with commercial and experimental ECHONET Lite devices. Our results show that the proposed solution effectively enables the smooth integration of ECHONET Lite devices into the Matter ecosystem, making it suitable for everyday use in smart home environments.

Advanced SDR Solutions for VHF and UHF Interoperability in Disaster Response

Advanced SDR Solutions for VHF and UHF Interoperability in Disaster Response

Offline robot programming assisted by task demonstration: an AutomationML interoperable solution for glass adhesive application and welding

ABSTRACT Robots have been successfully deployed in both traditional and novel manufacturing processes. However, they are still difficult to program by non-experts, which limits their accessibility to a wider range of potential users. Programming robots requires expertise in both robotics and the specific manufacturing process in which they are applied. Robot programs created offline often lack parameters that represent relevant manufacturing skills when executing a specific task. These skills encompass aspects like robot orientation and velocity. This paper introduces an intuitive robot programming system designed to capture manufacturing skills from task demonstrations performed by skilled workers. Demonstration data, including orientations and velocities of the working paths, are acquired using a magnetic tracking system fixed to the tools used by the worker. Positional data are extracted from CAD/CAM. Robot path poses are transformed into Cartesian space and validated in simulation, subsequently leading to the generation of robot programs. PathML, an AutomationML-based syntax, integrates robot and manufacturing data across the heterogeneous elements and stages of the manufacturing systems considered. Experiments conducted on the glass adhesive application and welding processes showcased the intuitive nature of the system, with path errors falling within the functional tolerance range.

OPO-CVI: design and implementation of an ocean profiling observation system for wave-powered vertical profiler following an ISO standard

This paper presents the design and implementation of an ISO-compliant ocean profiling observation system for wave-powered vertical profiler. This system aims to provide a comprehensive, scalable, and interoperable solution for high-resolution, real-time oceanic observation. As a part of this system, we introduce a wave-powered vertical profiler, known as “Wave Master,” designed to offer enhanced stability and reliability for long-term oceanic data collection. The core of the paper focuses on the Ocean Profiling Observation Complex Virtual Instrument (OPO-CVI), a comprehensive system developed in alignment with ISO 21851 standard. OPO-CVI seamlessly integrates data collection, transmission, storage, and visualization. Specifically, OPO-CVI addresses the challenges of information isolation, system rigidity, and lack of modularity in traditional ocean profiling methods by standardizing data formats and transmission protocols, allowing for seamless integration of new observation elements, and employing a modular architecture for enhanced scalability and reusability. By offering detailed technical insights into the OPO-CVI architecture and its compliance with ISO 21851 standard, this paper aims to contribute significantly to the advancement of standardized, efficient, and reliable oceanic observation systems.

Infusion pump innovation: Embracing change for patients and bottom lines.

Within the infusion delivery landscape, significant room exists for an improved experience with more intuitive and interoperable solutions. The majority of smart infusion pumps still rely on technology developed more than a decade ago. Many Canadian healthcare institutions regularly undergo a comprehensive re-evaluation of infusion fleets, to modernize infusion delivery for patients across the country. Amid the availability of new technologies with evidence demonstrating their ability to elevate the current standards of care, this article argues for the need for healthcare systems to prepare for, and embrace, change when it comes to new technologies. Clinical informatics consultant, Helen Edwards, delves into why new technologies are needed now more than ever. She shares her experience with the Ivenix Infusion System, capturing how it can help redefine clinical workflows, reduce costs across the entire healthcare continuum, and better support patient care. She also offers insights on how to effectively introduce new technologies and cultivate an environment that is likely to be open and adaptive to the change. As the Canadian healthcare landscape continues to evolve, the proactive adoption of new technologies will be a step towards advancing the outcomes for patients and the sustainability of Canadian healthcare infrastructures.

Recent Progress on the Convergence of the Internet of Things and Artificial Intelligence

Abstract: Artificial Intelligence of Things (AIoT) is the natural growth for both Artificial Intelligence (AI) and Internet of Things (IoT) as they are mutually gainful.. AI raise the value of the IoT through Machine Learning by transforming the data into useful information, although the IoT increases the value of AI through connectivity and data exchange. Hence, InSecTT – Intelligent Secure Trustable Things, a pan-European effort with 52 key partners from 12 countries (EU and Turkey), gives intelligent, secure and trustworthy systems for industrial purposes. This results in global cost-efficient solutions of intelligent, end-to-end secure, authentic connectivity and interoperability to bring the Internet of Things and Artificial Intelligence in sync. InSecTT targets at creating trust in AI-based intelligent systems and solutions as a major part of the AIoT. This paper provides an overview regarding the concept and ideas behind InSecTT and introduces the InSecTT Reference Architecture for infrastructure organization of AIoT use cases.

Development of Interoperability Principles for Disaster and Emergency Management System of Türkiye

Due to their complex nature, disasters and emergencies require a data-intensive management system in which many actors from different sectors participate and simultaneous processes are managed. Due to this complexity, there are problems in managing and sharing process services and geographic data effectively. The key to solving these problems is the introduction of a complete interoperability model. In this context, interoperability models based on existing international standards are analyzed in this study. FEI and EIF models are taken as basis in terms of disaster and emergency management interoperability requirements. Accordingly, the interoperability reference model was created in legal, organizational, semantic and technical frameworks to meet the interoperability levels. This general framework model has been evaluated in the service and data layers that need to be fully defined in disaster and emergency management phases, and a basic model including interoperability solutions for the service and data model has been created.

Electronic health record impact on data quality: An integrated review

Few studies have assessed the impact of Electronic Health Record (EHR) on data quality and how it has impacted timeliness, accuracy, availability, integrity, consistency and uniqueness of health data. Assessing the current gaps between electronic health record utilisation in relation to enhancing data quality can help to identify and recommend key measures to improve healthcare delivery. This review examines the impact of electronic health record on data quality, and proposes recommendations desirable to improving healthcare delivery. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Integrative Review Frameworks (IRF) were adapted as a sign post for the study. These frameworks guided literature search, data analysis and presentation of findings. Boolean AND/OR operators were combined with search terms to increase relevant search results. Six (6) electronic databases that were used for literature search are Scopus, Web of Science, Science Direct, PubMed, ProQuest and Google Scholar. Searched articles were between 2012 to 2022, with the exception of two articles on the Technology Acceptance Model (TAM) published in 1986 and 1975. EHR implementation impact key health outcomes and contribute to timely and complete data submission. Implementation of Electronic Health Systems (EHS) embellish consistency, completeness, accuracy and integrity of clinical data significantly through embedded interoperability solutions. By reducing the scope of manual reviews, integrating a technology that automates data integrity and quality checks into EHR may potentially lessen the strain of maintaining data quality. Our findings depict that interoperability of clinical data sources will ensure consistent, timely and available health data when using EHR. The automated data integrity and consistency checks in the EHR improve data quality. The study contributes to advancing the theory of Technology Acceptance Model (TAM) in electronic health records and its impact on data quality in healthcare delivery.

Recent Advances in Machine Learning for Network Automation in the O-RAN.

The evolution of network technologies has witnessed a paradigm shift toward open and intelligent networks, with the Open Radio Access Network (O-RAN) architecture emerging as a promising solution. O-RAN introduces disaggregation and virtualization, enabling network operators to deploy multi-vendor and interoperable solutions. However, managing and automating the complex O-RAN ecosystem presents numerous challenges. To address this, machine learning (ML) techniques have gained considerable attention in recent years, offering promising avenues for network automation in O-RAN. This paper presents a comprehensive survey of the current research efforts on network automation usingML in O-RAN.We begin by providing an overview of the O-RAN architecture and its key components, highlighting the need for automation. Subsequently, we delve into O-RAN support forML techniques. The survey then explores challenges in network automation usingML within the O-RAN environment, followed by the existing research studies discussing application of ML algorithms and frameworks for network automation in O-RAN. The survey further discusses the research opportunities by identifying important aspects whereML techniques can benefit.

Trust-minimized optimistic cross-rollup arbitrary message bridge

With the increasing acceptance and utilization of blockchain technology, a multitude of blockchain-based systems have emerged. Consequently, the need for interoperability among these systems has become paramount, particularly in a trustless manner. To enable decentralized and secure cross-chain applications for users, the establishment of a trust-minimized interoperability solution is imperative for homogeneous blockchain-based networks. This paper presents an analysis of the current state and challenges associated with interoperability between blockchain-based systems. Building upon previous research, we propose that the set of blockchain-based networks should be narrowed down based on the same settlement layer for supporting trust-minimized interoperability. Specifically, we concentrate on the cross-rollup functionality between rollups. We have devised and implemented two similar solutions to address the aforementioned interoperability problem, employing a trust-minimized optimistic approach. Through extensive experimentation, we compare our proposed solutions with existing cross-rollup bridges in terms of gas consumption, time complexity, and newly introduced trust assumptions. Our experimental investigations concentrate on the transmission of arbitrary data utilizing non-fungible tokens. The results reveal that one of our proposed solutions offers an optimal approach for cross-rollup communication between optimistic rollups.

Gateway-based Interoperability for Distributed Ledger Technology

Blockchain is a distributed ledger technology (DLT) to manage data in a decentralised way. During the last years, interoperability has become one of the main challenges within blockchain research as blockchains increasingly require integration between each other. Indeed, blockchains work by design in silos of information as interoperability is not a native feature. The main efforts in the field are focused on blockchains, such as Bitcoin and Ethereum. However, interoperability in DLT remains as an almost untouched area of work as they introduce additional requirements focusing on privacy and identity. Although there are some interoperability solutions for DLT, they are either high-level design proposals not providing concrete implementations or focus on interoperability issues between business applications and blockchain platforms. In this paper we propose a gateway-based platform-to-platform interoperability solution for DLT, which comprises a detailed solution design and a reference implementation. The proposal was assessed through the development of a social security case scenario and the evaluation through two interoperability frameworks. A reference implementation was built using two DLT: Hyperledger Fabric and Corda. The experimental results shows that it is possible to achieve technical interoperability between two heterogeneous DLT platforms using a gateway-based interoperability solution, relaxing decentralisation, data privacy, identity and authorisation management properties.

PLC orchestration automation to enhance human–machine integration in adaptive manufacturing systems

Current approaches to manufacturing must evolve to respond to increasing demands for short product life cycles and customised products. Adaptive manufacturing systems integrate advanced technologies, automation, and data-driven methodologies to develop adaptable, efficient, and responsive production processes. Central to this concept is the emphasis on human involvement and fostering synergy between human operators and the manufacturing system. Significant changes to the system’s controller are required to achieve adaptivity, with programmable logic controllers (PLCs) being a common controller type. After the necessary changes to the configuration of the manufacturing system, the PLC should be reconfigured to orchestrate the new required behaviour. Automated reconfiguration is vital to rapidly responding to change, but some changes cannot be entirely achieved without human input in collaboration with automated methods. Conventional practices in PLC programming include manual, repetitive coding practices subject to errors. As a result, to ensure operational safety, the changes must be tested before being deployed to operations, ensuring it is error-free. This paper presents a methodology to automatically reconfigure the simulation environment and controller in response to a new product request. We automate the PLC code generation and testing practices to support and free up the operators when performing repetitive manufacturing reconfiguration tasks. The methodology is based on human learning, software automation, customised program development, knowledge graphs, and Graph Neural Networks (GNNs). The presented solution is a generic, vendor-agnostic, and interoperable solution that facilitates information exchange among multiple heterogeneous environments. Lastly, we have validated the methodology as a proof of concept at an adaptive assembly cell at the University of Nottingham in the United Kingdom.

Immersive Experiences and XR: A Game Engine or Multimedia Streaming Problem?

Recent improvements in extended reality (XR) technology created an increase in XR products and solutions in the industry while raising new requirements for new or improved architectural concepts. This need can be particularly complex as XR applications often relate both to 3D geometric rendering and multimedia paradigms. This article outlines the main concepts relevant to XR, both from a game engineering and a multimedia streaming system perspective. XR requires new metadata and media/game orchestration to allow complex interaction between users, objects, and (volumetric) multimedia content, which also results in new requirements on synchronization (i.e., for global object state and positioning). Furthermore, the article presents the functional blocks needed in new XR system architectures and how they will glue both (game and media) spaces together. The discussion of functional components and architecture relates to the ongoing activities in relevant standardization bodies like Khronos, Moving Picture Experts Group (MPEG) and The 3rd Generation Partnership Project (3GPP). To make XR successful in the long term, the industry needs to agree on interoperable solutions and how to merge both game and media paradigms to allow complex multiuser XR applications.