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    Multilevel Goal Model for Decision-Making in UAS Visual Inspections in Construction and Infrastructure Projects

    Source: Journal of Management in Engineering:;2020:;Volume ( 036 ):;issue: 004
    Author:
    Sungjin Kim
    ,
    Javier Irizarry
    ,
    Ruth Kanfer
    DOI: 10.1061/(ASCE)ME.1943-5479.0000803
    Publisher: ASCE
    Abstract: Many studies have discussed unmanned aircraft system (UAS) applications for infrastructure conditions and construction project inspections. However, the industry currently faces significant challenges that hinder the use of this technology. UAS operational procedure is disjointed with regard to the inspection decision-making process. Moreover, training those responsible for UAS operations requires a great deal of time and cost. This study documents the job responsibilities and establishes goals for UAS operators in the construction and infrastructure domains through the use of goal-directed cognitive task analysis (GCTA). GCTA has been proven essential to enhancing training efficiency by revealing necessary areas of augmentation of information requirements related to UAS operation, such as situation awareness and decision criteria. The main goal of this study is to provide a better understanding of the task responsibilities and multilevel goals for operating a UAS. The findings of this study include three key personnel identified, their task domains, goals, and decision criteria, and situation awareness (SA) requirements. In the end, this study also instigates extensive discussion of the conceptual goal-directed decision-making process to support the realization of the goals of UAS applications. This study will help to enhance training performance and align UAS operational procedures and decision-making related to inspection tasks in the construction and infrastructure project environments.
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      Multilevel Goal Model for Decision-Making in UAS Visual Inspections in Construction and Infrastructure Projects

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4266111
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    • Journal of Management in Engineering

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    contributor authorSungjin Kim
    contributor authorJavier Irizarry
    contributor authorRuth Kanfer
    date accessioned2022-01-30T19:52:05Z
    date available2022-01-30T19:52:05Z
    date issued2020
    identifier other%28ASCE%29ME.1943-5479.0000803.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4266111
    description abstractMany studies have discussed unmanned aircraft system (UAS) applications for infrastructure conditions and construction project inspections. However, the industry currently faces significant challenges that hinder the use of this technology. UAS operational procedure is disjointed with regard to the inspection decision-making process. Moreover, training those responsible for UAS operations requires a great deal of time and cost. This study documents the job responsibilities and establishes goals for UAS operators in the construction and infrastructure domains through the use of goal-directed cognitive task analysis (GCTA). GCTA has been proven essential to enhancing training efficiency by revealing necessary areas of augmentation of information requirements related to UAS operation, such as situation awareness and decision criteria. The main goal of this study is to provide a better understanding of the task responsibilities and multilevel goals for operating a UAS. The findings of this study include three key personnel identified, their task domains, goals, and decision criteria, and situation awareness (SA) requirements. In the end, this study also instigates extensive discussion of the conceptual goal-directed decision-making process to support the realization of the goals of UAS applications. This study will help to enhance training performance and align UAS operational procedures and decision-making related to inspection tasks in the construction and infrastructure project environments.
    publisherASCE
    titleMultilevel Goal Model for Decision-Making in UAS Visual Inspections in Construction and Infrastructure Projects
    typeJournal Paper
    journal volume36
    journal issue4
    journal titleJournal of Management in Engineering
    identifier doi10.1061/(ASCE)ME.1943-5479.0000803
    page04020036
    treeJournal of Management in Engineering:;2020:;Volume ( 036 ):;issue: 004
    contenttypeFulltext
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