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.
Artificial intelligence in structural health management of existing bridges / Di Mucci, V. M.; Cardellicchio, A.; Ruggieri, S.; Nettis, A.; Reno, V.; Uva, G.. - In: AUTOMATION IN CONSTRUCTION. - ISSN 0926-5805. - 167:(2024). [10.1016/j.autcon.2024.105719]
Artificial intelligence in structural health management of existing bridges
Di Mucci V. M.;Cardellicchio A.;Ruggieri S.;Nettis A.;Uva G.
2024-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
