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工业5.0时代基于物联网的数字孪生框架。

IoT-Based Framework for Digital Twins in the Industry 5.0 Era.

作者信息

Awouda Ahmed, Traini Emiliano, Bruno Giulia, Chiabert Paolo

机构信息

Department of Management and Production Engineering, Politecnico di Torino, 10129 Turin, Italy.

出版信息

Sensors (Basel). 2024 Jan 17;24(2):594. doi: 10.3390/s24020594.

Abstract

Digital twins are considered the next step in IoT-based cyber-physical systems; they allow for the real-time monitoring of assets, and they provide a comprehensive understanding of a system behavior, allowing for data-driven insights and informed choices. However, no comprehensive framework exists for the development of IoT-based digital twins. Moreover, the existing frameworks do not consider the aspects introduced by the Industry 5.0 paradigm, such as sustainability, human-centricity, and resilience. This paper proposes a framework based on the one defined as the outcome of a project funded by the European Union between 2010 and 2013 called the IoT Architectural Reference Model (IoT-A or IoT-ARM), with the aim of the development and implementation of a standard IoT framework that includes digital twins. This framework establishes and implements a standardized collection of architectural instruments for modeling IoT systems in the 5.0 era, serving as a benchmark for the design and implementation of an IoT architecture focused on digital twins and enabling the sustainability, resilience, and human-centricity of the information system. Furthermore, a proof of concept of a monitoring digital twin for a vertical farming system has been developed to test the validity of the framework, and a discussion of applications in the manufacturing and service sectors is presented.

摘要

数字孪生被视为基于物联网的网络物理系统的下一步发展;它们允许对资产进行实时监控,并提供对系统行为的全面理解,从而实现数据驱动的见解和明智的选择。然而,目前还没有用于开发基于物联网的数字孪生的综合框架。此外,现有的框架没有考虑工业5.0范式所引入的方面,如可持续性、以人为本和弹性。本文提出了一个基于2010年至2013年由欧盟资助的一个项目成果所定义的框架,该项目称为物联网架构参考模型(IoT-A或IoT-ARM),旨在开发和实施一个包括数字孪生的标准物联网框架。这个框架建立并实施了一套标准化的架构工具集,用于对5.0时代的物联网系统进行建模,作为专注于数字孪生的物联网架构设计和实施的基准,并实现信息系统的可持续性、弹性和以人为本。此外,还开发了一个垂直农场系统监测数字孪生的概念验证来测试该框架的有效性,并讨论了在制造业和服务业中的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b877/10819514/449913c14d85/sensors-24-00594-g001.jpg

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