Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91424
PIRA download icon_1.1View/Download Full Text
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 SizeFormat 
1-s2.0-S2095809920303799-main.pdf1.2 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

16
Citations as of May 15, 2022

Downloads

2
Citations as of May 15, 2022

SCOPUSTM   
Citations

31
Citations as of May 20, 2022

WEB OF SCIENCETM
Citations

35
Citations as of May 19, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.