• Login
    View Item 
    •   DSpace Home
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    •   DSpace Home
    • ASCE
    • Journal of Computing in Civil Engineering
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Fusing Heterogeneous Information for Underground Utility Map Generation Based on Dempster-Shafer Theory

    Thumbnail
    View/Open
    %28ASCE%29CP.1943-5487.0000892.pdf (1.468Mb)
    Date
    2020
    Author
    Jiannan Cai
    JungHo Jeon
    Hubo Cai
    Shuai Li
    Metadata
    Show full item record
    Abstract
    Accurately mapping and labeling buried utilities is critical to managing massive urban underground infrastructure and preventing utility incidents. However, current spatial information regarding underground utilities is inconsistent, inaccurate, and uncertain, which is a root cause of numerous utility incidents. Information about underground utilities is usually provided by multiple sources, such as existing records and nondestructive testing technologies [e.g., ground-penetrating radar (GPR)]. A key challenge is the integration of imperfect data obtained from heterogeneous sources to create accurate underground utility maps. Aiming at accurately confirming the presence or absence of underground pipes, this study presents an information fusion method based on Dempster-Shafer (D-S) evidence theory to integrate both sensing and nonsensing data. The GPR and existing utility records serve as two independent information sources that provide evidence regarding the existence and configuration of buried utilities. The trust level of evidence provided by different sources is modeled as mass value, and practical guidance is proposed to quantitatively assign the mass value of individual data sources by considering various factors that affect the accuracy of each data source. By fusing the evidence from heterogeneous sources, the joint mass value is computed, based on which the state of pipes is inferred. Indoor experiments on three different scenarios demonstrate the efficacy of the proposed method. The results show that the proposed fusion approach leads to higher accuracy, precision, and recall in detecting pipes than using an individual data source. Furthermore, the robustness of the proposed mass value selection guidance is validated through sensitivity analysis, namely the fusion result remains stable when the mass value for an individual data source varies slightly.
    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4265260
    Collections
    • Journal of Computing in Civil Engineering

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV
     

     

    Browse

    All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    DSpace software copyright © 2002-2015  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    @mire NV