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作者:

Chen, Ning (Chen, Ning.) | Shi, Hongyu (Shi, Hongyu.) | Liu, Ruijun (Liu, Ruijun.) | Li, Yujie (Li, Yujie.) | Li, Ji (Li, Ji.) | Xu, Zijin (Xu, Zijin.) | Wang, Dawei (Wang, Dawei.) | Lu, Guoyang (Lu, Guoyang.) | Jing, Baohong (Jing, Baohong.) | Hou, Yue (Hou, Yue.)

收录:

EI Scopus SCIE

摘要:

Crack recognition is important in periodic pavement inspection and maintenance. The wide application of image recognition technology in daily inspection and maintenance makes the health monitoring of asphalt pavement defects more effective, both intelligently and sustainably. In this study, a mobile automatic system integrating fifth-generation wireless communication technology (5G), cloud computing, and artificial intelligence (AI) was proposed for transportation infrastructure object recognition. The original dataset contained 344 images of pavement defects, including longitudinal cracks, transverse cracks, alligator cracks, and broken road markings. Three lightweight algorithms for automatic pavement crack identification were used and compared, including MobileNetV2, ShuffleNetV2, and Res-Net50 networks, respectively. The results showed that the model based on ShuffieNetV2 achieved the best overall predictive accuracy (ACC = 95.52 percent). A mobile automatic monitoring system based on the cloud platform and Android framework was then established. With the help of 5G technology, the cloud-network-terminal' interconnection can be achieved to provide fast and stable information transmission between transportation infrastructure and road users. The proposed system provides an engineering reference for the transportation infrastructure inspection and maintenance using the 5G communication technology.

关键词:

Transportation Maintenance engineering Cloud computing Wireless communication 5G mobile communication Inspection Road traffic

作者机构:

  • [ 1 ] [Chen, Ning]Beijing Univ Technol, Beijing, Peoples R China
  • [ 2 ] [Xu, Zijin]Beijing Univ Technol, Beijing, Peoples R China
  • [ 3 ] [Hou, Yue]Beijing Univ Technol, Beijing, Peoples R China
  • [ 4 ] [Shi, Hongyu]China Acad Transportat Sci, Beijing, Peoples R China
  • [ 5 ] [Liu, Ruijun]Beijing Technol & Business Univ, Beijing, Peoples R China
  • [ 6 ] [Li, Yujie]Yangzhou Univ, Yangzhou, Peoples R China
  • [ 7 ] [Li, Ji]Swansea Univ, Swansea, Wales
  • [ 8 ] [Hou, Yue]Swansea Univ, Swansea, Wales
  • [ 9 ] [Wang, Dawei]Rhein Westfal TH Aachen, Aachen, Germany
  • [ 10 ] [Wang, Dawei]Harbin Inst Technol, Harbin, Peoples R China
  • [ 11 ] [Lu, Guoyang]City Univ Hong Kong, Hong Kong, Peoples R China
  • [ 12 ] [Jing, Baohong]Qingdao Yicheng Sichuang Link Things Technol Co LT, Qingdao, Peoples R China

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来源 :

IEEE WIRELESS COMMUNICATIONS

ISSN: 1536-1284

年份: 2023

期: 2

卷: 30

页码: 76-81

1 2 . 9 0 0

JCR@2022

ESI学科: COMPUTER SCIENCE;

ESI高被引阀值:19

被引次数:

WoS核心集被引频次:

SCOPUS被引频次: 5

ESI高被引论文在榜: 0 展开所有

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