Computer vision-based construction progress monitoring

被引:71
|
作者
Reja, Varun Kumar [1 ,2 ]
Varghese, Koshy [1 ]
Ha, Quang Phuc [2 ]
机构
[1] IIT Madras, BTCM Div, Dept Civil Engn, Chennai, India
[2] Univ Technol Sydney, Fac Engn & IT, Sydney, NSW 2007, Australia
关键词
Progress monitoring; Computer vision; Automated construction; Data acquisition; 3D reconstruction; As-built modelling; Point cloud; Scan to BIM; Literature review; Digital Twin; 3D BUILDING MODELS; SCAN-TO-BIM; POINT CLOUDS; RECONSTRUCTION; REGISTRATION; RECOGNITION; EXTRACTION; GENERATION; KNOWLEDGE; TRACKING;
D O I
10.1016/j.autcon.2022.104245
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Automating the process of construction progress monitoring through computer vision can enable effective control of projects. Systematic classification of available methods and technologies is necessary to structure this complex, multi-stage process. Using the PRISMA framework, relevant studies in the area were identified. The various concepts, tools, technologies, and algorithms reported by these studies were iteratively categorised, developing an integrated process framework for Computer-Vision-Based Construction Progress Monitoring (CVCPM). This framework comprises: data acquisition and 3D-reconstruction, as-built modelling, and progress assessment. Each stage is discussed in detail, positioning key studies, and concurrently comparing the methods used therein. The four levels of progress monitoring are defined and found to strongly influence all stages of the framework. The need for benchmarking CV-CPM pipelines and components are discussed, and potential research questions within each stage are identified. The relevance of CV-CPM to support emerging areas such as Digital Twin is also discussed.
引用
收藏
页数:17
相关论文
共 50 条
  • [1] Automated Computer Vision-Based Construction Progress Monitoring: A Systematic Review
    Rehman, Muhammad Sami Ur
    Shafiq, Muhammad Tariq
    Ullah, Fahim
    BUILDINGS, 2022, 12 (07)
  • [2] Computer vision-based interior construction progress monitoring: A literature review and future research directions
    Ekanayake, Biyanka
    Wong, Johnny Kwok-Wai
    Fini, Alireza Ahmadian Fard
    Smith, Peter
    AUTOMATION IN CONSTRUCTION, 2021, 127
  • [3] Automated Assembly Progress Monitoring in Modular Construction Factories Using Computer Vision-Based Instance Segmentation
    Panahi, Roshan
    Louis, Joseph
    Podder, Ankur
    Swanson, Colby
    Pless, Shanti
    COMPUTING IN CIVIL ENGINEERING 2023-DATA, SENSING, AND ANALYTICS, 2024, : 290 - 297
  • [4] A novel computer vision-based approach for monitoring safety harness use in construction
    Xu, Zhijing
    Huang, Jiajing
    Huang, Kan
    IET IMAGE PROCESSING, 2023, 17 (04) : 1071 - 1085
  • [5] Automated vision-based construction progress monitoring in built environment through digital twin
    Pal, Aritra
    Lin, Jacob J.
    Hsieh, Shang-Hsien
    Golparvar-Fard, Mani
    DEVELOPMENTS IN THE BUILT ENVIRONMENT, 2023, 16
  • [6] Computer Vision-Based Intelligent Monitoring of Disruptions due to Construction Machinery Arrival Delay
    Yan, Xuzhong
    Jin, Rui
    Zhang, Hong
    Gao, Hui
    Xu, Shuyuan
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2025, 39 (03)
  • [7] Computer Vision-Based Bridge Inspection and Monitoring: A Review
    Luo, Kui
    Kong, Xuan
    Zhang, Jie
    Hu, Jiexuan
    Li, Jinzhao
    Tang, Hao
    SENSORS, 2023, 23 (18)
  • [8] Review of Computer Vision-based Structural Displacement Monitoring
    Ye X.-W.
    Dong C.-Z.
    Zhongguo Gonglu Xuebao/China Journal of Highway and Transport, 2019, 32 (11): : 21 - 39
  • [9] A computer vision-based system for monitoring Vojta therapy
    Khan, Muhammad Hassan
    Helsper, Julien
    Farid, Muhammad Shahid
    Grzegorzek, Marcin
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2018, 113 : 85 - 95
  • [10] Application of computer vision for construction progress monitoring: a qualitative investigation
    Moragane, H. P. M. N. L. B.
    Perera, B. A. K. S.
    Palihakkara, Asha Dulanjalie
    Ekanayake, Biyanka
    CONSTRUCTION INNOVATION-ENGLAND, 2024, 24 (02): : 446 - 469