A Novel Building Construction Inspection Method Based on Naive Bayes Model by Fusing BIM and Lidar Point Cloud

被引:0
|
作者
Jiang, Boyu [1 ,2 ]
Fan, Liting [1 ]
Zhang, Yang [2 ,3 ]
Han, Yu [1 ,2 ]
Cheng, Zhongjiang [2 ]
机构
[1] Shenyang Jianzhu Univ, Mech Engn Sch, Shenyang 110168, Peoples R China
[2] Shenzhen Technol Univ, Sino German Coll Intelligent Mfg, Shenzhen 518118, Peoples R China
[3] Shenzhen Technol Univ, Mech Ind Key Lab Intelligent Robot Technol 3C, Shenzhen 518118, Peoples R China
来源
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2024, PT III | 2025年 / 15203卷
关键词
Construction monitoring; Point cloud comparison; BIM technology; Naive bayes classifier;
D O I
10.1007/978-981-96-0795-2_13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As the construction industry progresses and develops, construction inspection of the built environment plays a vital role in the success of a building project. This paper introduced a building construction quality monitoring method that combined building information modeling and LiDAR point cloud technology. The method first collected the point cloud data of the building environment, and preprocessed point cloud data including removing outliers and alignment; then, the point cloud generated by the BIM model was compared and analyzed with the actual point cloud to obtain the relative relationship between the two point clouds; finally, the results were determined by a Naive Bayes classification model to assess the construction quality. This method provided a complete set of solutions for construction quality verification, and promoted the construction industry to move towards intelligent and precise management.
引用
收藏
页码:167 / 184
页数:18
相关论文
共 50 条
  • [21] Denoising Method Based on Improved DBSCAN for Lidar Point Cloud
    Zhao, Zhe
    Zhou, Weilong
    Liang, Denghui
    Liu, Juntao
    Lee, Xiaobao
    IEEE ACCESS, 2024, 12 : 137656 - 137666
  • [22] Sustainable Application of Hybrid Point Cloud and BIM Method for Tracking Construction Progress
    Kim, Seungho
    Kim, Sangyong
    Lee, Dong-Eun
    SUSTAINABILITY, 2020, 12 (10)
  • [23] Depth-informed point cloud-to-BIM registration for construction inspection using augmented reality
    Liu, Han
    Liu, Donghai
    Chen, Junjie
    ADVANCED ENGINEERING INFORMATICS, 2024, 62
  • [24] MODEL RETRIEVAL BASED ON POINT CLOUD ENCODING OF AIRBORNE LIDAR
    Chen, Jyun-Yuan
    Hsu, Po-Chi
    Lin, Chao-Hung
    2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2012, : 4711 - 4713
  • [25] A Classification Method for Building Detection Based on LiDAR Point Clouds
    Zhou Mei
    Xia Bing
    Su Guozhong
    Tang Lingli
    Li Chanrong
    2009 JOINT URBAN REMOTE SENSING EVENT, VOLS 1-3, 2009, : 828 - 832
  • [26] Research on the Construction of BIM Visualization Model Based on 3D Laser Point Cloud Data
    Liu, Mao-hua
    You, Ying-chun
    Li, Man-wen
    Han, Zi-wei
    2018 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM 2018), 2018, 310 : 63 - 66
  • [27] A new method for building roof segmentation from airborne LiDAR point cloud data
    Kong, Deming
    Xu, Lijun
    Li, Xiaolu
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2013, 24 (09)
  • [28] Virtual construction method and application of building construction process based on BIM technology
    Wang Jinyu
    AGRO FOOD INDUSTRY HI-TECH, 2017, 28 (01): : 2256 - 2260
  • [29] Image-based Airborne LiDAR Point Cloud Encoding for 3D Building Model Retrieval
    Chen, Yi-Chen
    Lin, Chao-Hung
    XXIII ISPRS CONGRESS, COMMISSION VIII, 2016, 41 (B8): : 1237 - 1242
  • [30] Vehicle localization and navigation method based on LiDAR point cloud map
    Ma, Qinglu
    Bai, Feng
    Zhang, Jie
    Zou, Zheng
    Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2024, 32 (16): : 2537 - 2549