Multi-Task Intelligent Monitoring of Construction Safety Based on Computer Vision

被引:1
|
作者
Liu, Lingfeng [1 ]
Guo, Zhigang [1 ]
Liu, Zhengxiong [1 ]
Zhang, Yaolin [2 ]
Cai, Ruying [3 ]
Hu, Xin [4 ]
Yang, Ran [5 ]
Wang, Gang [3 ]
机构
[1] Shenzhen Municipal Grp Co Ltd, Shenzhen 518000, Peoples R China
[2] CCCC Property Hainan Co Ltd, Sanya 572000, Peoples R China
[3] Shenzhen Univ, Key Lab Resilient Infrastructures Coastal Cities, Shenzhen 518060, Peoples R China
[4] Chongqing Technol & Business Inst, Sch Urban Construct Engn, Chongqing 400067, Peoples R China
[5] CCDC Shuyu Engn Construct Co Ltd, Chengdu 610000, Peoples R China
基金
中国国家自然科学基金;
关键词
computer vision; construction safety; unsafe behaviors; intelligent monitoring; object detection; segmentation; pose; YOLO; WORKERS; FALLS;
D O I
10.3390/buildings14082429
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Effective safety management is vital for ensuring construction safety. Traditional safety inspections in construction heavily rely on manual labor, which is both time-consuming and labor-intensive. Extensive research has been conducted integrating computer-vision technologies to facilitate intelligent surveillance and improve safety measures. However, existing research predominantly focuses on singular tasks, while construction environments necessitate comprehensive analysis. This study introduces a multi-task computer vision technology approach for the enhanced monitoring of construction safety. The process begins with the collection and processing of multi-source video surveillance data. Subsequently, YOLOv8, a deep learning-based computer vision model, is adapted to meet specific task requirements by modifying the head component of the framework. This adaptation enables efficient detection and segmentation of construction elements, as well as the estimation of person and machine poses. Moreover, a tracking algorithm integrates these capabilities to continuously monitor detected elements, thereby facilitating the proactive identification of unsafe practices on construction sites. This paper also presents a novel Integrated Excavator Pose (IEP) dataset designed to address the common challenges associated with different single datasets, thereby ensuring accurate detection and robust application in practical scenarios.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] 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
  • [2] Computer vision techniques for construction safety and health monitoring
    Seo, JoonOh
    Han, SangUk
    Lee, SangHyun
    Kim, Hyoungkwan
    ADVANCED ENGINEERING INFORMATICS, 2015, 29 (02) : 239 - 251
  • [3] Computer vision applications in construction safety assurance
    Fang, Weili
    Ding, Lieyun
    Love, Peter E. D.
    Luo, Hanbin
    Li, Heng
    Pena-Mora, Feniosky
    Zhong, Botao
    Zhou, Cheng
    AUTOMATION IN CONSTRUCTION, 2020, 110
  • [4] Rigorous analysis of safety rules for vision intelligence-based monitoring at construction jobsites
    Lee, Doyeop
    Khan, Numan
    Park, Chansik
    INTERNATIONAL JOURNAL OF CONSTRUCTION MANAGEMENT, 2023, 23 (10) : 1768 - 1778
  • [5] Vision-Based Construction Safety Monitoring Utilizing Temporal Analysis to Reduce False Alarms
    Zaidi, Syed Farhan Alam
    Yang, Jaehun
    Abbas, Muhammad Sibtain
    Hussain, Rahat
    Lee, Doyeop
    Park, Chansik
    BUILDINGS, 2024, 14 (06)
  • [6] Pyramid Swin Transformer for Multi-task: Expanding to More Computer Vision Tasks
    Wang, Chenyu
    Endo, Toshio
    Hirofuchi, Takahiro
    Ikegami, Tsutomu
    ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2023, 2023, 14124 : 53 - 65
  • [7] THE BIOLOGICAL INTELLIGENT MONITORING OF WATER POLLUTION BASED ON COMPUTER MACHINE VISION
    Feng, Yingwei
    Xiao, Ruixue
    FRESENIUS ENVIRONMENTAL BULLETIN, 2022, 31 (3A): : 3663 - 3673
  • [8] 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)
  • [9] Computer vision-based construction progress monitoring
    Reja, Varun Kumar
    Varghese, Koshy
    Ha, Quang Phuc
    AUTOMATION IN CONSTRUCTION, 2022, 138
  • [10] Advancing construction site workforce safety monitoring through BIM and computer vision integration
    Kulinan, Almo Senja
    Park, Minsoo
    Aung, Pa Pa Win
    Cha, Gichun
    Park, Seunghee
    AUTOMATION IN CONSTRUCTION, 2024, 158