Show simple item record

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


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record