62 research outputs found

    Service-oriented architecture for device lifecycle support in industrial automation

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    Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores Especialidade: Robótica e Manufactura IntegradaThis thesis addresses the device lifecycle support thematic in the scope of service oriented industrial automation domain. This domain is known for its plethora of heterogeneous equipment encompassing distinct functions, form factors, network interfaces, or I/O specifications supported by dissimilar software and hardware platforms. There is then an evident and crescent need to take every device into account and improve the agility performance during setup, control, management, monitoring and diagnosis phases. Service-oriented Architecture (SOA) paradigm is currently a widely endorsed approach for both business and enterprise systems integration. SOA concepts and technology are continuously spreading along the layers of the enterprise organization envisioning a unified interoperability solution. SOA promotes discoverability, loose coupling, abstraction, autonomy and composition of services relying on open web standards – features that can provide an important contribution to the industrial automation domain. The present work seized industrial automation device level requirements, constraints and needs to determine how and where can SOA be employed to solve some of the existent difficulties. Supported by these outcomes, a reference architecture shaped by distributed, adaptive and composable modules is proposed. This architecture will assist and ease the role of systems integrators during reengineering-related interventions throughout system lifecycle. In a converging direction, the present work also proposes a serviceoriented device model to support previous architecture vision and goals by including embedded added-value in terms of service-oriented peer-to-peer discovery and identification, configuration, management, as well as agile customization of device resources. In this context, the implementation and validation work proved not simply the feasibility and fitness of the proposed solution to two distinct test-benches but also its relevance to the expanding domain of SOA applications to support device lifecycle in the industrial automation domain

    Lot-Size One Production

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    Demystifying Internet of Things Security

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    Break down the misconceptions of the Internet of Things by examining the different security building blocks available in Intel Architecture (IA) based IoT platforms. This open access book reviews the threat pyramid, secure boot, chain of trust, and the SW stack leading up to defense-in-depth. The IoT presents unique challenges in implementing security and Intel has both CPU and Isolated Security Engine capabilities to simplify it. This book explores the challenges to secure these devices to make them immune to different threats originating from within and outside the network. The requirements and robustness rules to protect the assets vary greatly and there is no single blanket solution approach to implement security. Demystifying Internet of Things Security provides clarity to industry professionals and provides and overview of different security solutions What You'll Learn Secure devices, immunizing them against different threats originating from inside and outside the network Gather an overview of the different security building blocks available in Intel Architecture (IA) based IoT platforms Understand the threat pyramid, secure boot, chain of trust, and the software stack leading up to defense-in-depth Who This Book Is For Strategists, developers, architects, and managers in the embedded and Internet of Things (IoT) space trying to understand and implement the security in the IoT devices/platforms

    A Complex Event Processing System for Monitoring of Manufacturing Systems

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    Future manufacturing systems will require to process large amounts of complex data due to a rising demand on visibility and vertical integration of factory floor devices with higher level systems. Systems contained in higher layers of the business model are rapidly moving towards a Service Oriented Architecture, inducing a tendency to push Web Technologies down to the factory floor level. Evidence of this trend is the addition of Web Services at the device level with Device Profile for Web Services and the transition of OPC based on COM/DCOM communication to OPC-UA based on Web Services. DPWS and OPC-UA are becoming nowadays the preferred options to provide on a device level, service-oriented solutions capable to extend with an Event Driven Architecture into manufacturing systems. This thesis provides an implementation of a factory shop floor monitor based on Complex Event Processing for event-driven manufacturing processes. Factory shop monitors are particularly used to inform the workshop personnel via alarms, notifications and, visual aids about the performance and status of a manufacturing process. This work abstracts the informative value of the event-cloud surrounding the factory shop floor by processing its content against rules and formulas to convert it to valuable pieces of information that can be exposed to business monitors and dashboards. As a result, a system with a generic framework for integrating heterogeneous sources was reached, transforming simple data into alarms and complex events containing a specific context within the manufacturing process

    Advancing IoT Platforms Interoperability

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    The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

    Data Spaces

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    This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

    Advancing IoT Platforms Interoperability

    Get PDF
    The IoT European Platforms Initiative (IoT-EPI) projects are addressing the topic of Internet of Things and Platforms for Connected Smart Objects and aim to deliver an IoT extended into a web of platforms for connected devices and objects that supports smart environments, businesses, services and persons with dynamic and adaptive configuration capabilities. The specific areas of focus of the research activities are architectures and semantic interoperability, which reliably cover multiple use cases. The goal is to deliver dynamically-configured infrastructure and integration platforms for connected smart objects covering multiple technologies and multiple intelligent artefacts. The IoT-EPI ecosystem has been created with the objective of increasing the impact of the IoT-related European research and innovation, including seven European promising projects on IoT platforms: AGILE, BIG IoT, INTER-IoT, VICINITY, SymbIoTe, bIoTope, and TagItSmart.This white paper provides an insight regarding interoperability in the IoT platforms and ecosystems created and used by IoT-EPI. The scope of this document covers the interoperability aspects, challenges and approaches that cope with interoperability in the current existing IoT platforms and presents some insights regarding the future of interoperability in this context. It presents possible solutions, and a possible IoT interoperability platform architecture

    Data Spaces

    Get PDF
    This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical
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