Semantic-Enhanced Digital Twin for Industrial Working Environments
Loading...
Access rights
openAccess
CC BY
CC BY
publishedVersion
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Date
2025
Major/Subject
Mcode
Degree programme
Language
en
Pages
18
Series
Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings, pp. 3-20, Communications in Computer and Information Science ; Volume 2328
Abstract
Real-time data from diverse Internet of Things (IoT) sensors (such as cameras, temperature, light, and air quality sensors) is essential for monitoring smart manufacturing environments. However, efficiently perceiving, integrating, and interpreting this data remains a challenge, as it involves dealing with heterogeneous data formats, ensuring data accuracy, and providing real-time analytics. This paper proposes a semantic-enhanced Digital Twin (DT) to address these complexities and aims to offer a comprehensive view of industrial working environments. The paper first presents a conceptual overview of the semantic-enhanced DT architecture, followed by a detailed description of the system architecture, encompassing edge, cloud, and interface modules. Additionally, the implementation of the entire system is presented. The results demonstrate the feasibility of the proposed DT, showing its potential for deployment in real-world scenarios.Description
Publisher Copyright: © The Author(s) 2025.
Keywords
Digital Twin, Industrial working environment, Internet of Things, Semantic model
Other note
Citation
Yang, C, Guo, Q, Yu, H, Chen, Y, Taleb, T & Tammi, K 2025, Semantic-Enhanced Digital Twin for Industrial Working Environments . in M Presser, A Skarmeta, S Krco & A González Vidal (eds), Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings . Communications in Computer and Information Science, vol. 2328, Springer, pp. 3-20, International Summit on the Global Internet of Things and Edge Computing, Brussels, Belgium, 24/09/2024 . https://doi.org/10.1007/978-3-031-78572-6_1