A study on adjustment method of finishing work schedule based on image detection for high-rise building construction
Author(s) -
Taekyu Ko,
Joonghwan Shin,
SoonWook Kwon,
S. Callejas-Sandoval,
Heesung Park,
JaeWoo Park
Publication year - 2018
Publication title -
creative construction conference 2018 - proceedings
Language(s) - English
Resource type - Conference proceedings
DOI - 10.3311/ccc2018-035
Subject(s) - schedule , work schedule , computer science , work (physics) , image (mathematics) , computer vision , artificial intelligence , architectural engineering , engineering , mechanical engineering , operating system
As recent buildings have been getting higher and larger, the finishing work management has become a key factor for successful projects. Although many finishing work management techniques have been trying to set up a measureable scheduling plan at early stages before construction lift installation, but schedule adjustments according to site condition and construction progress are inevitable because there are many unexpected variables. To develop the assistance tool for finishing work management techniques such as TACT or LOB(Line of balance), in this study, we suggested image-detection(helmet detection) based labor counting method. The internet protocol cameras at each inside of construction lift cages collect and send photography data to processing server. And through image detection processing using photography data, it is possible to count the number of workers put into each finishing work. The worker count result is used for comparison with the existing finishing work schedule. This study has served as a key lead of lift monitoring based construction process management. Therefore, it is anticipated to settle as a system based data-centric construction management technique in the field. © 2018 The Authors. Published by Diamond Congress Ltd. Peer-review under responsibility of the scientific committee of the Creative Construction Conference 2018.
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