Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/91424
| Title: | The state-of-the-art review on applications of intrusive sensing, image processing techniques, and machine learning methods in pavement monitoring and analysis | Authors: | Hou, Y Li, Q Zhang, C Lu, G Ye, Z Chen, Y Wang, L Cao, D |
Issue Date: | Jun-2021 | Source: | Engineering, June 2021, v. 7, no. 6, p. 845-856 | Abstract: | In modern transportation, pavement is one of the most important civil infrastructures for the movement of vehicles and pedestrians. Pavement service quality and service life are of great importance for civil engineers as they directly affect the regular service for the users. Therefore, monitoring the health status of pavement before irreversible damage occurs is essential for timely maintenance, which in turn ensures public transportation safety. Many pavement damages can be detected and analyzed by monitoring the structure dynamic responses and evaluating road surface conditions. Advanced technologies can be employed for the collection and analysis of such data, including various intrusive sensing techniques, image processing techniques, and machine learning methods. This review summarizes the state-of-the-art of these three technologies in pavement engineering in recent years and suggests possible developments for future pavement monitoring and analysis based on these approaches. | Keywords: | Image processing techniques Intrusive sensing Machine learning methods Pavement monitoring and analysis The state-of-the-art review |
Publisher: | Gaodeng Jiaoyu Chubanshe | Journal: | Engineering | ISSN: | 2095-8099 | EISSN: | 2096-0026 | DOI: | 10.1016/j.eng.2020.07.030 | Rights: | © 2021 THE AUTHORS. Published by Elsevier LTD on behalf of Chinese Academy of Engineering andHigher Education Press Limited Company. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). The following publication Hou, Y., Li, Q., Zhang, C., Lu, G., Ye, Z., Chen, Y., ... & Cao, D. (2021). The state-of-the-art review on applications of intrusive sensing, image processing techniques, and machine learning methods in pavement monitoring and analysis. Engineering is available at https://doi.org/10.1016/j.eng.2020.07.030 |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S2095809920303799-main.pdf | 1.2 MB | Adobe PDF | View/Open |
Access
View full-text via PolyU eLinks 
Page views
42
Last Week
1
1
Last month
Citations as of Sep 17, 2023
Downloads
5
Citations as of Sep 17, 2023
SCOPUSTM
Citations
104
Citations as of Sep 21, 2023
WEB OF SCIENCETM
Citations
98
Citations as of Sep 21, 2023
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.