The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0
Xiao Wang1; Yutong Wang2; Jing Yang2,3; Xiaofeng Jia4; Lijun Li5; Weiping Ding6; Fei-Yue Wang2,3,7
Source PublicationInformation Fusion
ISSN1566-2535
2024-07
Volume107Pages:1-16
Corresponding AuthorWang, Xiao(xiao.wang@ahu.edu.cn)
Abstract

As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in parallel with the actual industrial processes to offer "Human-Centric" Safe, Secure, Sustainable, Sensitive, Service, and Smartness "6S" manufacturing solutions. Industrial metaverses not only visualize the process of productivity in a dynamic and evolutional way, but also provide an immersive laboratory experimental environment for optimizing and remodeling the process. Besides, the customized user needs that are hidden in social media data can be discovered by social computing technologies, which introduces an input channel for building the whole social manufacturing process including industrial metaverses. This makes the fusion of multi-source data cross Cyber–Physical–Social Systems (CPSS) the foundational and key challenge. This work firstly proposes a multi-source-data-fusion-driven operational architecture for industrial metaverses on the basis of conducting a comprehensive literature review on the state-of-the-art multi-source data fusion methods. The advantages and disadvantages of each type of method are analyzed by considering the fusion mechanisms and application scenarios. Especially, we combine the strengths of deep learning and knowledge graphs in scalability and parallel computation to enable our proposed framework the ability of prescriptive optimization and evolution. This integration can address the shortcomings of deep learning in terms of explainability and fact fabrication, as well as overcoming the incompleteness and the challenges of construction and maintenance inherent in knowledge graphs. The effectiveness of the proposed architecture is validated through a parallel weaving case study. In the end, we discuss the challenges and future directions of multi-source data fusion cross CPSS for industrial metaverses and social manufacturing in Industries 5.0.

KeywordMulti-source data fusion CPSS Industrial metaverses Parallel manufacturing Social manufacturing
DOI10.1016/j.inffus.2024.102321
WOS KeywordOF-THE-ART ; INFORMATION FUSION ; BLOCKCHAIN ; FRAMEWORK ; REPRESENTATION ; PERSPECTIVES ; INTELLIGENCE ; PREDICTION ; SOCIETIES ; PARADIGM
Indexed BySCI
Language英语
Funding ProjectPrediction and Guidance Effect of Social Media on Traffic Congestion and Its Derivative Events ; National Natural Science Foundation of China[62173329]
Funding OrganizationPrediction and Guidance Effect of Social Media on Traffic Congestion and Its Derivative Events ; National Natural Science Foundation of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:001203802100001
PublisherELSEVIER
Sub direction classification多模态智能
planning direction of the national heavy laboratory多模态协同感认知智能的机制机理与数学建模
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57288
Collection多模态人工智能系统全国重点实验室_平行智能技术与系统团队
Corresponding AuthorXiao Wang
Affiliation1.School of Artificial Intelligence, Anhui University
2.Institute of Automation, Chinese Academy of Sciences
3.School of Artificial Intelligence, University of Chinese Academy of Sciences
4.National Engineering Laboratory for Big Data Collaborative Security Technology
5.School of Automation, Southeast University
6.School of Information Science and Technology, Nantong University
7.Faculty of Innovation Engineering, Macau University of Science and Technology
Recommended Citation
GB/T 7714
Xiao Wang,Yutong Wang,Jing Yang,et al. The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0[J]. Information Fusion,2024,107:1-16.
APA Xiao Wang.,Yutong Wang.,Jing Yang.,Xiaofeng Jia.,Lijun Li.,...&Fei-Yue Wang.(2024).The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0.Information Fusion,107,1-16.
MLA Xiao Wang,et al."The survey on multi-source data fusion in cyber-physical-social systems: Foundational infrastructure for industrial metaverses and industries 5.0".Information Fusion 107(2024):1-16.
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