Digital Twin for Railway: A Comprehensive Survey
Digital transformation has been prioritized in the railway industry to bring automation to railway operations. Digital Twin (DT) technology has recently gained attention in the railway industry to fulfill this goal. Contemporary researchers argue that DT can be advantageous in Railway manufacturing...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10292659/ |
| _version_ | 1797635423163383808 |
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| author | Sara Ghaboura Rahatara Ferdousi Fedwa Laamarti Chunsheng Yang Abdulmotaleb El Saddik |
| author_facet | Sara Ghaboura Rahatara Ferdousi Fedwa Laamarti Chunsheng Yang Abdulmotaleb El Saddik |
| author_sort | Sara Ghaboura |
| collection | DOAJ |
| description | Digital transformation has been prioritized in the railway industry to bring automation to railway operations. Digital Twin (DT) technology has recently gained attention in the railway industry to fulfill this goal. Contemporary researchers argue that DT can be advantageous in Railway manufacturing logistics to planning and scheduling. Although underlying technologies of DT, e.g., modelling, computer vision, and the Internet of Things, have been studied for various railway industry applications, the DT has been least explored in the context of railways. Thus, in this paper, we aim to understand the state-of-the-art of DT for railway (DTR), for advanced railway systems. Besides, this survey clarifies how DT can serve the railway twin system designers and developers. As DTR is still in its early adoption stage, there is hardly any clear direction to identify the technologies for specific DTR applications. Therefore, based on our findings we present a taxonomy for DTR for designers and developers. Finally, we describe potential challenges, pitfalls, and opportunities in DTR for future researchers. |
| first_indexed | 2024-03-11T12:20:57Z |
| format | Article |
| id | doaj.art-93a8a54e57604c4e80661d3e381240a4 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-11T12:20:57Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-93a8a54e57604c4e80661d3e381240a42023-11-07T00:01:59ZengIEEEIEEE Access2169-35362023-01-011112023712025710.1109/ACCESS.2023.332704210292659Digital Twin for Railway: A Comprehensive SurveySara Ghaboura0https://orcid.org/0009-0000-4906-429XRahatara Ferdousi1https://orcid.org/0000-0003-1143-2370Fedwa Laamarti2Chunsheng Yang3https://orcid.org/0000-0003-3043-5622Abdulmotaleb El Saddik4https://orcid.org/0000-0002-7690-8547Computer Vision Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab EmiratesMultimedia Communications Research Laboratory (MCRLab), University of Ottawa, Ottawa, CanadaComputer Vision Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab EmiratesNational Research Council Canada, Ottawa, CanadaComputer Vision Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab EmiratesDigital transformation has been prioritized in the railway industry to bring automation to railway operations. Digital Twin (DT) technology has recently gained attention in the railway industry to fulfill this goal. Contemporary researchers argue that DT can be advantageous in Railway manufacturing logistics to planning and scheduling. Although underlying technologies of DT, e.g., modelling, computer vision, and the Internet of Things, have been studied for various railway industry applications, the DT has been least explored in the context of railways. Thus, in this paper, we aim to understand the state-of-the-art of DT for railway (DTR), for advanced railway systems. Besides, this survey clarifies how DT can serve the railway twin system designers and developers. As DTR is still in its early adoption stage, there is hardly any clear direction to identify the technologies for specific DTR applications. Therefore, based on our findings we present a taxonomy for DTR for designers and developers. Finally, we describe potential challenges, pitfalls, and opportunities in DTR for future researchers.https://ieeexplore.ieee.org/document/10292659/Digital twinrailwaymodellingstructural health monitoringartificial intelligencesafety |
| spellingShingle | Sara Ghaboura Rahatara Ferdousi Fedwa Laamarti Chunsheng Yang Abdulmotaleb El Saddik Digital Twin for Railway: A Comprehensive Survey IEEE Access Digital twin railway modelling structural health monitoring artificial intelligence safety |
| title | Digital Twin for Railway: A Comprehensive Survey |
| title_full | Digital Twin for Railway: A Comprehensive Survey |
| title_fullStr | Digital Twin for Railway: A Comprehensive Survey |
| title_full_unstemmed | Digital Twin for Railway: A Comprehensive Survey |
| title_short | Digital Twin for Railway: A Comprehensive Survey |
| title_sort | digital twin for railway a comprehensive survey |
| topic | Digital twin railway modelling structural health monitoring artificial intelligence safety |
| url | https://ieeexplore.ieee.org/document/10292659/ |
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