A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools

IF 34.4 1区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

IEEE Communications Surveys and Tutorials Pub Date : 2023-07-20 DOI:10.1109/COMST.2023.3297395

Hansong Xu;Jun Wu;Qianqian Pan;Xinping Guan;Mohsen Guizani

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引用次数: 7

Abstract

Digital twin for the industrial Internet of Things (DT-IIoT) creates a high-fidelity, fine-grained, low-cost digital replica of the cyber-physical integrated Internet for industry. Powered by artificial intelligence (AI) and security technologies, DT-IIoT provides advanced features such as real-time monitoring, predictive maintenance, remote diagnostics, and rapid response for smart IIoT systems. A systematic review of key enabling technologies such as digital twin, AI, and blockchain is essential to develop DT-IIoT and reveal pitfalls. This paper reviews the preliminaries, real-world applications, architectures and models of digital twin-driven IIoT. In addition, advanced technologies for intelligent and secure DT-IIoT are investigated, including state-of-the-art AI solutions such as transfer learning and federated learning, as well as blockchain-based security solutions. Moreover, software tools for high-fidelity digital twin modeling are proposed. A case study on reinforcement learning-based integrated-control, communication, and computing (3C) design is developed to demonstrate the AI-driven intelligent DT-IIoT. Finally, this paper outlines the prospective applications, challenges, and integrations with ABCDE (i.e., AI, Blockchain, cloud computing, big data, edge computing) as the future directions.

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工业物联网数字孪生研究:应用、技术与工具

工业物联网数字孪生(DT-IIoT)为工业网络物理集成互联网创建了高保真、细粒度、低成本的数字复制品。在人工智能(AI)和安全技术的支持下，DT-IIoT为智能IIoT系统提供了实时监控、预测性维护、远程诊断和快速响应等先进功能。对数字孪生、人工智能和区块链等关键使能技术的系统审查对于开发DT-IIoT和揭示陷阱至关重要。本文综述了数字双驱动工业物联网的初步研究、实际应用、架构和模型。此外，还研究了智能和安全DT-IIoT的先进技术，包括最先进的人工智能解决方案，如迁移学习和联邦学习，以及基于区块链的安全解决方案。此外，还提出了高保真数字孪生模型建模的软件工具。以基于强化学习的集成控制、通信和计算(3C)设计为例，展示了人工智能驱动的智能DT-IIoT。最后，本文概述了未来ABCDE(即人工智能、区块链、云计算、大数据、边缘计算)的应用前景、挑战和集成方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Communications Surveys and Tutorials COMPUTER SCIENCE, INFORMATION SYSTEMS-TELECOMMUNICATIONS

CiteScore

80.20

自引率

2.50%

发文量

审稿时长

6 months

期刊介绍： IEEE Communications Surveys & Tutorials is an online journal published by the IEEE Communications Society for tutorials and surveys covering all aspects of the communications field. Telecommunications technology is progressing at a rapid pace, and the IEEE Communications Society is committed to providing researchers and other professionals the information and tools to stay abreast. IEEE Communications Surveys and Tutorials focuses on integrating and adding understanding to the existing literature on communications, putting results in context. Whether searching for in-depth information about a familiar area or an introduction into a new area, IEEE Communications Surveys & Tutorials aims to be the premier source of peer-reviewed, comprehensive tutorials and surveys, and pointers to further sources. IEEE Communications Surveys & Tutorials publishes only articles exclusively written for IEEE Communications Surveys & Tutorials and go through a rigorous review process before their publication in the quarterly issues. A tutorial article in the IEEE Communications Surveys & Tutorials should be designed to help the reader to become familiar with and learn something specific about a chosen topic. In contrast, the term survey, as applied here, is defined to mean a survey of the literature. A survey article in IEEE Communications Surveys & Tutorials should provide a comprehensive review of developments in a selected area, covering its development from its inception to its current state and beyond, and illustrating its development through liberal citations from the literature. Both tutorials and surveys should be tutorial in nature and should be written in a style comprehensible to readers outside the specialty of the article.