• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Intelligent hazard identification: Dynamic visibility measurement of construction equipment operators

    Thumbnail
    View/Open
    JAGADEVRAY-DISSERTATION-2014.pdf (19.29Mb)
    Date
    2014-03-26
    Author
    Ray, Soumitry J.
    Metadata
    Show full item record
    Abstract
    Struck-by fatalities involving heavy equipment such as trucks and cranes accounted for 24.6% of the fatalities between 1997-2007 in the construction industry. Limited visibility due to blind spots and travel in reverse direction are the primary causes of these fatalities. Blind spots are spaces surrounding an equipment that are invisible to the equipment operator. Thus, a hazard is posed to the ground personnel working in the blind spaces of an equipment operator. This research presents a novel approach to intelligently identify potential hazards posed to workers operating near an equipment by determining the visible and blind space regions of an equipment operator in real-time. A depth camera is used to estimate the head posture of the equipment operator and continuously track the head location and orientation using Random Forests algorithm. The head posture information is then integrated with point cloud data of the construction equipment to determine both the visible and the blindspots region of the equipment operator using Ray-Casting algorithm. Simulation and field experiments were carried out to validate this approach in controlled and uncontrolled environment respectively. Research findings demonstrate the potential of this approach to enhance safety performance by detecting hazardous proximity situations.
    URI
    http://hdl.handle.net/1853/51968
    Collections
    • Georgia Tech Theses and Dissertations [23403]
    • School of Computational Science and Engineering Theses and Dissertations [92]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology