Semantic-Enhanced Digital Twin for Industrial Working Environments

Chao Yang; Qize Guo; Hao Yu; Yan Chen; Tarik Taleb; Kari Tammi

doi:10.1007/978-3-031-78572-6_1

Semantic-Enhanced Digital Twin for Industrial Working Environments

Chao Yang^*, Qize Guo, Hao Yu, Yan Chen, Tarik Taleb, Kari Tammi

^*Tämän työn vastaava kirjoittaja

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

4 Lataukset (Pure)

Abstrakti

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.

Alkuperäiskieli	Englanti
Otsikko	Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings
Toimittajat	Mirko Presser, Antonio Skarmeta, Srdjan Krco, Aurora González Vidal
Kustantaja	Springer
Sivut	3-20
Sivumäärä	18
ISBN (painettu)	978-3-031-78571-9
DOI - pysyväislinkit	https://doi.org/10.1007/978-3-031-78572-6_1
Tila	Julkaistu - 2025
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	International Summit on the Global Internet of Things and Edge Computing - Brussels, Belgia Kesto: 24 syysk. 2024 → 25 syysk. 2024 Konferenssinumero: 1

Julkaisusarja

Nimi	Communications in Computer and Information Science
Vuosikerta	2328
ISSN (painettu)	1865-0929
ISSN (elektroninen)	1865-0937

Conference

Conference	International Summit on the Global Internet of Things and Edge Computing
Lyhennettä	GIECS
Maa/Alue	Belgia
Kaupunki	Brussels
Ajanjakso	24/09/2024 → 25/09/2024

Pääsy asiakirjaan

10.1007/978-3-031-78572-6_1Lisenssi: CC BY

978-3-031-78572-6_1Final published version, 3,41 MBLisenssi: CC BY

Muut tiedostot ja linkit

Linkki julkaisuun Scopuksessa

Necoverse: Next Generation Training, Design and Operation Environment Utilizing Industrial Metaverse
Tammi, K. (Vastuullinen tutkija)
01/03/2023 → 28/02/2025
Projekti: Business Finland: Strategic centres for science, technology and innovation (SHOK)

Siteeraa tätä

Yang, C., Guo, Q., Yu, H., Chen, Y., Taleb, T., & Tammi, K. (2025). Semantic-Enhanced Digital Twin for Industrial Working Environments. teoksessa M. Presser, A. Skarmeta, S. Krco, & A. González Vidal (Toimittajat), Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings (Sivut 3-20). (Communications in Computer and Information Science; Vuosikerta 2328). Springer. https://doi.org/10.1007/978-3-031-78572-6_1

Yang, Chao ; Guo, Qize ; Yu, Hao et al. / Semantic-Enhanced Digital Twin for Industrial Working Environments. Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings. Toimittaja / Mirko Presser ; Antonio Skarmeta ; Srdjan Krco ; Aurora González Vidal. Springer, 2025. Sivut 3-20 (Communications in Computer and Information Science).

@inproceedings{de5eb61b9c7d4386963ed1408fb975df,

title = "Semantic-Enhanced Digital Twin for Industrial Working Environments",

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.",

keywords = "Digital Twin, Industrial working environment, Internet of Things, Semantic model",

author = "Chao Yang and Qize Guo and Hao Yu and Yan Chen and Tarik Taleb and Kari Tammi",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2025.; International Summit on the Global Internet of Things and Edge Computing, GIECS ; Conference date: 24-09-2024 Through 25-09-2024",

year = "2025",

doi = "10.1007/978-3-031-78572-6_1",

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Yang, C, Guo, Q, Yu, H, Chen, Y, Taleb, T & Tammi, K 2025, Semantic-Enhanced Digital Twin for Industrial Working Environments. julkaisussa M Presser, A Skarmeta, S Krco & A González Vidal (toim), Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings. Communications in Computer and Information Science, Vuosikerta 2328, Springer, Sivut 3-20, International Summit on the Global Internet of Things and Edge Computing, Brussels, Belgia, 24/09/2024. https://doi.org/10.1007/978-3-031-78572-6_1

Semantic-Enhanced Digital Twin for Industrial Working Environments. / Yang, Chao; Guo, Qize; Yu, Hao et al.
Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings. toim. / Mirko Presser; Antonio Skarmeta; Srdjan Krco; Aurora González Vidal. Springer, 2025. s. 3-20 (Communications in Computer and Information Science; Vuosikerta 2328).

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussa › Conference article in proceedings › Scientific › vertaisarvioitu

TY - GEN

T1 - Semantic-Enhanced Digital Twin for Industrial Working Environments

AU - Yang, Chao

AU - Guo, Qize

AU - Yu, Hao

AU - Chen, Yan

AU - Taleb, Tarik

AU - Tammi, Kari

N1 - Conference code: 1

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

KW - Digital Twin

KW - Industrial working environment

KW - Internet of Things

KW - Semantic model

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PB - Springer

T2 - International Summit on the Global Internet of Things and Edge Computing

Y2 - 24 September 2024 through 25 September 2024

ER -

Yang C, Guo Q, Yu H, Chen Y, Taleb T, Tammi K. Semantic-Enhanced Digital Twin for Industrial Working Environments. julkaisussa Presser M, Skarmeta A, Krco S, González Vidal A, toimittajat, Global Internet of Things and Edge Computing Summit - First Global Summit, GIECS 2024, Proceedings. Springer. 2025. s. 3-20. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-78572-6_1