{"title":"A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools","authors":"Hansong Xu;Jun Wu;Qianqian Pan;Xinping Guan;Mohsen Guizani","doi":"10.1109/COMST.2023.3297395","DOIUrl":null,"url":null,"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.","PeriodicalId":55029,"journal":{"name":"IEEE Communications Surveys and Tutorials","volume":"25 4","pages":"2569-2598"},"PeriodicalIF":34.4000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Communications Surveys and Tutorials","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10188847/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
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.
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.
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