Development of advanced progress recognition algorithms for construction monitoring

This approach presents an innovative computer vision application in construction progress monitoring. It facilitates timely decision-making throughout the project lifecycle and offers a practical alternative to manual CPM methods. Using YOLOv8 for automated CPM is a novel contribution to construction project management, potentially impacting the successful completion.

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Publication Details

Journal
PLoS ONE
Published
2025-10-09
DOI
https://doi.org/10.1371/journal.pone.0333262
Primary Topic
Infrastructure Maintenance and Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Development of advanced progress recognition algorithms for construction monitoring

Jun Zhang, Ye Zhijie, Lai Yingdong, Lin Zhijun
PLoS ONE
Infrastructure Maintenance and Monitoring
article

Development of advanced progress recognition algorithms for construction monitoring

Jun Zhang, Ye Zhijie, Lai Yingdong, Lin Zhijun
article en

Abstract

This approach presents an innovative computer vision application in construction progress monitoring. It facilitates timely decision-making throughout the project lifecycle and offers a practical alternative to manual CPM methods. Using YOLOv8 for automated CPM is a novel contribution to construction project management, potentially impacting the successful completion.

PLoS ONEVol. 20(10)
Power Grid Corporation (India) (IN)
Openalex Percentile: Top 70%
Infrastructure Maintenance and Monitoring
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Development of advanced progress recognition algorithms for construction monitoring — Jun Zhang, Ye Zhijie, et al. · PLoS ONE (2025) | TGRS Research Map | TGRS