Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review
Civil infrastructure assets’ contribution to countries’ economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, exp...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/25/1/59 |
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| author | Zhiyan Sun Sanduni Jayasinghe Amir Sidiq Farham Shahrivar Mojtaba Mahmoodian Sujeeva Setunge |
| author_facet | Zhiyan Sun Sanduni Jayasinghe Amir Sidiq Farham Shahrivar Mojtaba Mahmoodian Sujeeva Setunge |
| author_sort | Zhiyan Sun |
| collection | DOAJ |
| description | Civil infrastructure assets’ contribution to countries’ economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure. However, these methods lack reliability due to the need for instrumentation calibration and reliance on subjective visual judgments. Digital twin (DT) technology digitally replicates existing infrastructure, offering significant potential for real-time intelligent monitoring and assessment of structural health. This study reviews the existing applications of DTs across various sectors. It proposes an approach for developing DT applications in civil infrastructure, including using the Internet of Things, data acquisition, and modelling, together with the platform requirements and challenges that may be confronted during DT development. This comprehensive review is a state-of-the-art review of advancements and challenges in DT technology for intelligent monitoring and maintenance of civil infrastructure. |
| format | Article |
| id | doaj-art-1653033eaaa64cc4a8c16a0fad483473 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-1653033eaaa64cc4a8c16a0fad4834732025-01-10T13:20:44ZengMDPI AGSensors1424-82202024-12-012515910.3390/s25010059Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive ReviewZhiyan Sun0Sanduni Jayasinghe1Amir Sidiq2Farham Shahrivar3Mojtaba Mahmoodian4Sujeeva Setunge5School of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaSchool of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaSchool of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaSchool of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaSchool of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaSchool of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, AustraliaCivil infrastructure assets’ contribution to countries’ economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure. However, these methods lack reliability due to the need for instrumentation calibration and reliance on subjective visual judgments. Digital twin (DT) technology digitally replicates existing infrastructure, offering significant potential for real-time intelligent monitoring and assessment of structural health. This study reviews the existing applications of DTs across various sectors. It proposes an approach for developing DT applications in civil infrastructure, including using the Internet of Things, data acquisition, and modelling, together with the platform requirements and challenges that may be confronted during DT development. This comprehensive review is a state-of-the-art review of advancements and challenges in DT technology for intelligent monitoring and maintenance of civil infrastructure.https://www.mdpi.com/1424-8220/25/1/59digital twincivil infrastructurestructural health monitoringvirtual modelasset management |
| spellingShingle | Zhiyan Sun Sanduni Jayasinghe Amir Sidiq Farham Shahrivar Mojtaba Mahmoodian Sujeeva Setunge Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review Sensors digital twin civil infrastructure structural health monitoring virtual model asset management |
| title | Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review |
| title_full | Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review |
| title_fullStr | Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review |
| title_full_unstemmed | Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review |
| title_short | Approach Towards the Development of Digital Twin for Structural Health Monitoring of Civil Infrastructure: A Comprehensive Review |
| title_sort | approach towards the development of digital twin for structural health monitoring of civil infrastructure a comprehensive review |
| topic | digital twin civil infrastructure structural health monitoring virtual model asset management |
| url | https://www.mdpi.com/1424-8220/25/1/59 |
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