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RIS-aided smart manufacturing : information transmission and machine health monitoring
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Hoang, Tiep M., Dinh-Van, Son, Barn, Balbir, Trestian, Ramona and Nguyen, Huan X. (2022) RIS-aided smart manufacturing : information transmission and machine health monitoring. IEEE Internet of Things Journal, 9 (22). pp. 22930-22943. doi:10.1109/JIOT.2022.3187189 ISSN 2327-4662.
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WRAP-RIS-aided-smart-manufacturing-information-transmission-and-machine-health-monitoring-Dinh-Van-22.pdf - Accepted Version - Requires a PDF viewer. Download (12Mb) | Preview |
Official URL: https://doi.org/10.1109/JIOT.2022.3187189
Abstract
This paper proposes a novel industrial Internet-of-Things framework to monitor the machine health conditions (MHCs) in a smart factory. The framework utilises reconfigurable intelligent surface (RIS) to address propagation blockages while employing a novel power mapping scheme and an autoencoder to facilitate the transmission and classification of the MHCs. Analytical and numerical analyses are then performed to study the ergodic capacity (primary information) and the MHC accuracy (secondary information) in terms of the RIS size (K) and the transmit power (P). We observe that the accuracy of detecting MHCs does not change significantly with K and P, implying that the MHC alerts can be efficiently conveyed in parallel with the primary information. By contrast, a careful choice of different power mapping levels is necessary in order to achieve the two main goals: i) reasonably high data rate for primary transmission and ii) high accuracy for secondary MHC information.
Item Type: | Journal Article | ||||||||||||
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Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||||||
Library of Congress Subject Headings (LCSH): | Internet of things, Industrial engineering, Industry 4.0 , Digital twins (Computer simulation) , Manufacturing processes -- Technological innovations, Machine learning , 5G mobile communication systems | ||||||||||||
Journal or Publication Title: | IEEE Internet of Things Journal | ||||||||||||
Publisher: | IEEE | ||||||||||||
ISSN: | 2327-4662 | ||||||||||||
Official Date: | 15 November 2022 | ||||||||||||
Dates: |
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Volume: | 9 | ||||||||||||
Number: | 22 | ||||||||||||
Number of Pages: | 14 | ||||||||||||
Page Range: | pp. 22930-22943 | ||||||||||||
DOI: | 10.1109/JIOT.2022.3187189 | ||||||||||||
Status: | Peer Reviewed | ||||||||||||
Publication Status: | Published | ||||||||||||
Reuse Statement (publisher, data, author rights): | © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | ||||||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||||||
Date of first compliant deposit: | 21 June 2022 | ||||||||||||
Date of first compliant Open Access: | 22 June 2022 | ||||||||||||
RIOXX Funder/Project Grant: |
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