394 research outputs found

    Design and management of image processing pipelines within CPS : Acquired experience towards the end of the FitOptiVis ECSEL Project

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    Cyber-Physical Systems (CPSs) are dynamic and reactive systems interacting with processes, environment and, sometimes, humans. They are often distributed with sensors and actuators, characterized for being smart, adaptive, predictive and react in real-time. Indeed, image- and video-processing pipelines are a prime source for environmental information for systems allowing them to take better decisions according to what they see. Therefore, in FitOptiVis, we are developing novel methods and tools to integrate complex image- and video-processing pipelines. FitOptiVis aims to deliver a reference architecture for describing and optimizing quality and resource management for imaging and video pipelines in CPSs both at design- and run-time. The architecture is concretized in low-power, high-performance, smart components, and in methods and tools for combined design-time and run-time multi-objective optimization and adaptation within system and environment constraints.Peer reviewe

    Smart Agents in Industrial Cyber–Physical Systems

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    Agents enabling cyber-physical production systems

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    In order to be prepared for future challenges facing the industrial production domain, Cyber-Physical Production Systems (CPPS) consisting of intelligent entities which collaborate and exchange information globally are being proclaimed recently as part of Industrie 4.0. In this article the requirements of CPPS and abilities of agents as enabling technology are discussed. The applicability of agents for realizing CPPS is exemplarily shown based on three selected use cases with different requirements regarding real-time and dependability. The paper finally concludes with opportunities and open research issues that need to be faced in order to achieve agent-based CPPSs.info:eu-repo/semantics/publishedVersio

    Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions

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    Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensive survey work on the use of XAI for IoT. To bridge this lacking, in this paper, we address the XAI frameworks with a focus on their characteristics and support for IoT. We illustrate the widely-used XAI services for IoT applications, such as security enhancement, Internet of Medical Things (IoMT), Industrial IoT (IIoT), and Internet of City Things (IoCT). We also suggest the implementation choice of XAI models over IoT systems in these applications with appropriate examples and summarize the key inferences for future works. Moreover, we present the cutting-edge development in edge XAI structures and the support of sixth-generation (6G) communication services for IoT applications, along with key inferences. In a nutshell, this paper constitutes the first holistic compilation on the development of XAI-based frameworks tailored for the demands of future IoT use cases.Comment: 29 pages, 7 figures, 2 tables. IEEE Open Journal of the Communications Society (2022

    Digital Twins for an Industrial Internet of Things Platform

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    Com o avanço da Indústria 4.0 e do surgimento de novas tecnologias de informação e comunicação tais como o IIoT (Industrial Internet of Things), o sector industrial tem procurado cada vez mais, evoluir as suas linhas de produção de modo a atingir a maior eficiência de produção possível. Aliado ao conceito IIoT, o termo Digital Twin e CPS (Cyber Physical System) começam a ganhar elevada relevância em vários sectores, nomeadamente no sector industrial. Apesar de serem conceitos que se podem confundir, o conceito de DT e CPS são aplicados em diferentes domínios. O conceito de CPS relaciona-se com a conexão de duas direções que é possível estabelecer entre o meio físico e o meio digital. Ele utiliza a rede IoT para capturar a informação do meio físico através de sensores e controladores e com esta informação, é possível no meio digital tornar a réplica mais inteligente a fim de conseguir reproduzir o comportamento da entidade física. O conceito de DT é um pouco menos abstrato, comparado com o conceito de CPS, e é o DT que implementa o CPS. O DT utiliza as funcionalidades do CPS para realizar modelos de simulação das entidades físicas de forma a conseguir espelhar a geometria e o comportamento da mesma no meio digital. Com estes modelos digitais é possível realizar uma monitorização e controlo em tempo real das entidades físicas. De forma a aplicar estes conceitos, esta dissertação tem como principal objetivo a implementação de um DT capaz de replicar o comportamento de uma determinada entidade física no meio digital. Dessa forma, através da aplicação web Jurassic Park como plataforma IoT, a dissertação pretende adicionar um conjunto de novas funcionalidades de controlo e monitorização à sua interface-gráfica, de modo a que o utilizador consiga não só observar em tempo real a variação de valores de variáveis previamente subscritas mas também controlar alguns eventos que também foram selecionados pelo utilizador previamente

    A connective framework to support the lifecycle of cyber-physical production systems

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    The potential benefits of the adoption of cyber-physical production systems (CPPSs) and their significant role in enabling smart manufacturing is well recognized today. However, it is less clear how such CPPS can be most effectively and consistently engineered and maintained throughout their lifecycle due to the existing divide in the information technology (IT) and operational technology (OT) landscape and ad hoc integration practices that result in inconsistent data and data models at various levels of manufacturing processes. The work presented in this article addresses this problem by envisioning a connective framework to support the engineering of CPPS through the use of a set of digital twins consistent with the real system throughout its lifecycle, not just used in the design and deployment phases. A review of the latest perspectives on using digital integration frameworks, methods, and solutions for lifecycle engineering of CPPS is provided in this article. This article demonstrates how a suitable framework, named SIMPLE, can be realized to effectively address the lack of consistent data models throughout the engineering lifecycle, including implementation details and example cases developed by the authors at the Warwick Manufacturing Group (WMG) in selected industrial sectors. Consideration is given to supporting cyber-to-physical systems' connectivity and extendable engineering toolsets, forming the basis for multidisciplinary digital engineering environments. Key discussion points include the role and importance of effective integration of IT and OT, suitable frameworks for integration and collaboration
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