Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art
In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are making big changes to the way traditional structural health monitoring (SHM) is done. Also, the capacity, flexibility, and robustness of artificial intelligence (AI) techniques for solving complex real-...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9858154/ |
| _version_ | 1826938528086360064 |
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| author | Raffaele Zinno Sina Shaffiee Haghshenas Giuseppe Guido Alessandro VItale |
| author_facet | Raffaele Zinno Sina Shaffiee Haghshenas Giuseppe Guido Alessandro VItale |
| author_sort | Raffaele Zinno |
| collection | DOAJ |
| description | In the age of the smart city, things like the Internet of Things (IoT) and big data analytics are making big changes to the way traditional structural health monitoring (SHM) is done. Also, the capacity, flexibility, and robustness of artificial intelligence (AI) techniques for solving complex real-world problems have led to an increasing interest in applying these methods to SHM systems of infrastructures in recent years. Therefore, an analytical evaluation of recent advancements in SHM for infrastructures appears to be important. The bridge is one of the significant transportation infrastructures where existing environmental and destructive variables can have a negative impact on the structure’s life and health. The SHM system for bridges in different stages of their life cycle, such as construction, development, management, and maintenance, is seen as a complementary part of intelligent transportation systems (ITS). The main goal of this study is to look at how AI can be used to improve the current state of the art in data-driven SHM systems for bridges, including conceptual frameworks, advantages, and challenges, as well as existing approaches. This article presents an overview of the role of AI in data-driven SHM systems for bridges in the future. Finally, some potential research possibilities in AI-assisted SHM are also emphasized and detailed. |
| first_indexed | 2024-04-12T23:35:14Z |
| format | Article |
| id | doaj.art-9d8a8b1053ad4f508fc96b352a41422b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2025-02-17T18:58:25Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-9d8a8b1053ad4f508fc96b352a41422b2024-12-11T00:01:56ZengIEEEIEEE Access2169-35362022-01-0110880588807810.1109/ACCESS.2022.31994439858154Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-ArtRaffaele Zinno0Sina Shaffiee Haghshenas1https://orcid.org/0000-0003-2859-3920Giuseppe Guido2Alessandro VItale3Department of Environmental Engineering, University of Calabria, Rende, ItalyDepartment of Civil Engineering, University of Calabria, Rende, ItalyDepartment of Civil Engineering, University of Calabria, Rende, ItalyDepartment of Civil Engineering, University of Calabria, Rende, ItalyIn the age of the smart city, things like the Internet of Things (IoT) and big data analytics are making big changes to the way traditional structural health monitoring (SHM) is done. Also, the capacity, flexibility, and robustness of artificial intelligence (AI) techniques for solving complex real-world problems have led to an increasing interest in applying these methods to SHM systems of infrastructures in recent years. Therefore, an analytical evaluation of recent advancements in SHM for infrastructures appears to be important. The bridge is one of the significant transportation infrastructures where existing environmental and destructive variables can have a negative impact on the structure’s life and health. The SHM system for bridges in different stages of their life cycle, such as construction, development, management, and maintenance, is seen as a complementary part of intelligent transportation systems (ITS). The main goal of this study is to look at how AI can be used to improve the current state of the art in data-driven SHM systems for bridges, including conceptual frameworks, advantages, and challenges, as well as existing approaches. This article presents an overview of the role of AI in data-driven SHM systems for bridges in the future. Finally, some potential research possibilities in AI-assisted SHM are also emphasized and detailed.https://ieeexplore.ieee.org/document/9858154/Structural health monitoringthe Internet of Thingsartificial intelligencedata-drivenbridgeintelligent transportation systems |
| spellingShingle | Raffaele Zinno Sina Shaffiee Haghshenas Giuseppe Guido Alessandro VItale Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art IEEE Access Structural health monitoring the Internet of Things artificial intelligence data-driven bridge intelligent transportation systems |
| title | Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art |
| title_full | Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art |
| title_fullStr | Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art |
| title_full_unstemmed | Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art |
| title_short | Artificial Intelligence and Structural Health Monitoring of Bridges: A Review of the State-of-the-Art |
| title_sort | artificial intelligence and structural health monitoring of bridges a review of the state of the art |
| topic | Structural health monitoring the Internet of Things artificial intelligence data-driven bridge intelligent transportation systems |
| url | https://ieeexplore.ieee.org/document/9858154/ |
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