Artificial intelligence in structural health management of existing bridges

被引:40
作者
Di Mucci, Vincenzo Mario [1 ]
Cardellicchio, Angelo [2 ]
Ruggieri, Sergio [1 ]
Nettis, Andrea [1 ]
Reno, Vito [2 ]
Uva, Giuseppina [1 ]
机构
[1] Polytech Univ Bari, DICATECH Dept, Via Orabona 4, Bari, Italy
[2] Natl Res Council Italy, Inst Intelligent Ind Technol & Syst Adv Mfg STIIMA, Via Amendola 122D O, Bari, Italy
关键词
Existing bridges; Structural health management; Artificial intelligence; Structural health monitoring; Computer vision; Risk assessment; INSPECTION;
D O I
10.1016/j.autcon.2024.105719
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The paper presents a systematic review about the use of artificial intelligence (AI) in the field of structural health management of existing bridges. Using the PRISMA protocol, 81 journal articles were analysed. Three areas of investigation were addressed: (1) use of computer vision (CV) to automatize visual inspection of existing bridges; (b) use of AI with data provided by sensors employed in structural health monitoring (SHM); (c) use of AI for enhancing prediction of existing bridges deterioration, to improve risk estimation. The findings indicated that while the first two areas are covered by the scientific literature, the most intriguing challenges regard the use of AI in the field of bridge performance and risk assessment, in which new technologies could be exploited for predicting structural decay over time and residual life. This synthesis could significantly contribute to facilitate the indispensable fusion between the traditional civil-structural engineering and the contemporary technological progresses.
引用
收藏
页数:24
相关论文
共 50 条
[41]   A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines [J].
Nguyen, Khanh T. P. ;
Medjaher, Kamal ;
Tran, Do T. .
ARTIFICIAL INTELLIGENCE REVIEW, 2023, 56 (04) :3659-3709
[42]   Editorial: Structural Health Monitoring of Bridges [J].
Hoult, Neil A. ;
Glisic, Branko .
FRONTIERS IN BUILT ENVIRONMENT, 2020, 6
[43]   A review of artificial intelligence methods for engineering prognostics and health management with implementation guidelines [J].
Khanh T. P. Nguyen ;
Kamal Medjaher ;
Do T. Tran .
Artificial Intelligence Review, 2023, 56 :3659-3709
[44]   Artificial Intelligence in Gerontology: Data-Driven Health Management and Precision Medicine [J].
Zhang, S. ;
Wu, L. ;
Zhao, Z. ;
Masso, J. R. Fernandez ;
Chen, M. .
ADVANCES IN GERONTOLOGY, 2024, 14 (03) :97-110
[45]   Artificial Intelligence Based Sentiment Analysis for Health Crisis Management in Smart Cities [J].
Hilal, Anwer Mustafa ;
Alfurhood, Badria Sulaiman ;
Al-Wesabi, Fahd N. ;
Hamza, Manar Ahmed ;
Al Duhayyim, Mesfer ;
Iskandar, Huda G. .
CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 71 (01) :143-157
[46]   Framework for Structural Health Monitoring of Steel Bridges by Computer Vision [J].
Marchewka, Adam ;
Ziolkowski, Patryk ;
Aguilar-Vidal, Victor .
SENSORS, 2020, 20 (03)
[47]   Research on the Application of Artificial Intelligence in Public Health Management: Leveraging Artificial Intelligence to Improve COVID-19 CT Image Diagnosis [J].
He, Tiancheng ;
Liu, Hong ;
Zhang, Zhihao ;
Li, Chao ;
Zhou, Youmei .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2023, 20 (02)
[48]   Artificial intelligence, human intelligence, and the future of public health [J].
Bhattacharya, Sudip .
AIMS PUBLIC HEALTH, 2022, 9 (04) :644-650
[49]   Artificial Intelligence in Health Care - A Study on Perceptions of and Readiness for Artificial Intelligence in Health-care Professionals [J].
Tezpal, Manvinder ;
Ghosh, Subhodeep ;
Lalwani, Radhika ;
Yadav, Jyoti ;
Yadav, Arun Kumar .
JOURNAL OF MARINE MEDICAL SOCIETY, 2024, 26 (03) :376-381
[50]   Patterns in management research on artificial intelligence: A longitudinal analysis using structural topic modeling [J].
Dahlke, Johannes ;
Ebersberger, Bernd .
JOURNAL OF EVOLUTIONARY ECONOMICS, 2025,