RIS-aided smart manufacturing: information transmission and machine health monitoring

Hoang, Tiep M., Son, Dinh-Van, Barn, Balbir ORCID logoORCID: https://orcid.org/0000-0002-7251-5033, Trestian, Ramona ORCID logoORCID: https://orcid.org/0000-0003-3315-3081 and Nguyen, Huan X. ORCID logoORCID: https://orcid.org/0000-0002-4105-2558 (2022) RIS-aided smart manufacturing: information transmission and machine health monitoring. IEEE Internet of Things Journal . ISSN 2327-4662 [Article] (Published online first) (doi:10.1109/JIOT.2022.3187189)

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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: Article
Sustainable Development Goals:
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 35357
Notes on copyright: © 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.
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Depositing User: Ramona Trestian
Date Deposited: 05 Jul 2022 10:31
Last Modified: 17 Feb 2023 15:05
URI: https://eprints.mdx.ac.uk/id/eprint/35357

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