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    Quantifying the Effectiveness of IoT Technologies for Accident Prevention

    Source: Journal of Management in Engineering:;2020:;Volume ( 036 ):;issue: 005
    Author:
    Chang Jae Yeo
    ,
    Jung Ho Yu
    ,
    Youngcheol Kang
    DOI: 10.1061/(ASCE)ME.1943-5479.0000825
    Publisher: ASCE
    Abstract: The Internet of Things (IoT) has attracted attention in recent years as a way to prevent construction site accidents. Although various IoT technologies have been tested for the purpose of safety management, few have been implemented in actual projects. One possible reason is that the effectiveness of these technologies has rarely been calculated. In this study, a method for quantitatively evaluating the effectiveness of IoT technologies for accident prevention is presented. Taking the domino theory of accident causation into account, this method has three aspects: the degree of the causes of accidents that an IoT technology prevents, association between accident types and their causes, and frequency of each accident type. To quantify these, two different types of survey were conducted, and statistical records about construction accidents by type were used. To test the applicability of this method, the effectiveness of two IoT technologies was calculated. The method successfully quantified how much each technology contributes to preventing certain types of accident as well as the overall accident-prevention effect. The proposed method can enable practitioners to assess the effectiveness of certain IoT technologies, which will be useful in justifying investments in the technology. The method will lead to deploying more IoT technologies for safety management, which will eventually contribute to decreasing accidents in the construction industry.
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      Quantifying the Effectiveness of IoT Technologies for Accident Prevention

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4267124
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    contributor authorChang Jae Yeo
    contributor authorJung Ho Yu
    contributor authorYoungcheol Kang
    date accessioned2022-01-30T20:47:29Z
    date available2022-01-30T20:47:29Z
    date issued9/1/2020 12:00:00 AM
    identifier other%28ASCE%29ME.1943-5479.0000825.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4267124
    description abstractThe Internet of Things (IoT) has attracted attention in recent years as a way to prevent construction site accidents. Although various IoT technologies have been tested for the purpose of safety management, few have been implemented in actual projects. One possible reason is that the effectiveness of these technologies has rarely been calculated. In this study, a method for quantitatively evaluating the effectiveness of IoT technologies for accident prevention is presented. Taking the domino theory of accident causation into account, this method has three aspects: the degree of the causes of accidents that an IoT technology prevents, association between accident types and their causes, and frequency of each accident type. To quantify these, two different types of survey were conducted, and statistical records about construction accidents by type were used. To test the applicability of this method, the effectiveness of two IoT technologies was calculated. The method successfully quantified how much each technology contributes to preventing certain types of accident as well as the overall accident-prevention effect. The proposed method can enable practitioners to assess the effectiveness of certain IoT technologies, which will be useful in justifying investments in the technology. The method will lead to deploying more IoT technologies for safety management, which will eventually contribute to decreasing accidents in the construction industry.
    publisherASCE
    titleQuantifying the Effectiveness of IoT Technologies for Accident Prevention
    typeJournal Paper
    journal volume36
    journal issue5
    journal titleJournal of Management in Engineering
    identifier doi10.1061/(ASCE)ME.1943-5479.0000825
    page12
    treeJournal of Management in Engineering:;2020:;Volume ( 036 ):;issue: 005
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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