Da, Y, Gao, Y ORCID: 0000-0001-7310-1476, Li, Y, Ren, D, Liu, K, Brás, A
ORCID: 0000-0002-6292-2073 and Shaw, A
ORCID: 0000-0001-5961-2464
(2025)
Advances in smart technologies and materials for automated asphalt pavement inspection: Toward transport infrastructure digitalisation.
Automation in Construction, 180.
p. 106523.
ISSN 0926-5805
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Abstract
The digitalisation of transport infrastructure helps extend pavement service life by enabling timely maintenance based on real-time data from automated inspection. This paper aims to review recent advancements in smart technologies and materials for the structural health monitoring (SHM) of asphalt pavements. Smart monitoring technologies are discussed by analysing their capability in the real-time automated inspection of early-stage pavement internal distress. Furthermore, smart pavement materials, particularly self-sensing asphalt materials, are reviewed in terms of their functionalities, fabrication and electrical characterisation. Finally, applications and challenges of self-sensing asphalt pavements are evaluated, including their implementation, engineering performance, and life cycle assessment. It is concluded that self-sensing asphalt materials provide an effective solution for real-time automated inspection of the early-stage internal distress in pavements. Artificial intelligence (AI) can facilitate the practical implementation of self-sensing asphalt pavement systems integrated with smart materials, management information systems, and intelligent control systems.
Item Type: | Article |
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Uncontrolled Keywords: | 4005 Civil Engineering; 40 Engineering; 33 Built Environment and Design; 3302 Building; 9 Industry, Innovation and Infrastructure; 09 Engineering; 12 Built Environment and Design; Building & Construction; 33 Built environment and design; 40 Engineering |
Subjects: | T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General) T Technology > TH Building construction |
Divisions: | Civil Engineering and Built Environment |
Publisher: | Elsevier BV |
Date of acceptance: | 3 September 2025 |
Date of first compliant Open Access: | 13 October 2025 |
Date Deposited: | 13 Oct 2025 14:46 |
Last Modified: | 13 Oct 2025 15:00 |
DOI or ID number: | 10.1016/j.autcon.2025.106523 |
URI: | https://researchonline.ljmu.ac.uk/id/eprint/27323 |
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