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contributor authorArash Shahi
contributor authorMahdi Safa
contributor authorCarl T. Haas
contributor authorJeffrey S. West
date accessioned2017-05-08T22:31:31Z
date available2017-05-08T22:31:31Z
date copyrightNovember 2015
date issued2015
identifier other48437446.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/82021
description abstractThis paper presents a process management framework for multisensory data fusion for the purpose of tracking the progress of construction activity. The developed framework facilitates the required type of data fusion at any given point in the construction progress, reliably and efficiently. Data are acquired from high-frequency automated technologies such as three-dimensional (3D) imaging and ultrawideband (UWB) positioning, in addition to foreman reports, schedule information, and other information sources. The results of validation through a detailed field implementation project show that the developed framework for fusing volumetric, positioning, and project control data can successfully address the challenges associated with fusing multisensory data by tracking activities rather than objects, a feature that offers superior capability, efficiency, and accuracy over the length of the project. Other contributions of this research include the development of fusion processes that are performed at higher levels of data fusion instead of traditional low-level fusion algorithms, thus supporting decision-making processes and a number of automated construction management applications, such as construction progress tracking, earned-value estimation, and schedule updating.
publisherAmerican Society of Civil Engineers
titleData Fusion Process Management for Automated Construction Progress Estimation
typeJournal Paper
journal volume29
journal issue6
journal titleJournal of Computing in Civil Engineering
identifier doi10.1061/(ASCE)CP.1943-5487.0000436
treeJournal of Computing in Civil Engineering:;2015:;Volume ( 029 ):;issue: 006
contenttypeFulltext


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