Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/74170
Title: Location-based measurement and visualization for interdependence network on construction sites
Authors: Yang, X 
Luo, X
Li, H 
Luo, X
Guo, H
Keywords: Construction activities
Interdependence network
Location-based service
Quantitative measurement
Issue Date: 2017
Publisher: Elsevier
Source: Advanced engineering informatics, 2017, v. 34, p. 36-45 How to cite?
Journal: Advanced engineering informatics 
Abstract: Appropriately assigning workers to tasks is vitally important in project management. To do this, project managers need to objectively and effectively measure and visualize the spatiotemporal orders of real construction process as well as coordination structure of the workforce. However, currently there is no method/tool available to project managers to represent spatiotemporal orders of construction processes. To address this issue, this paper presents a novel approach to measuring the real spatiotemporal order of onsite tasks as well as the task interdependence by an interdependence network. This approach extracts the distance of workspace distributions as a key interdependence indicator from historical location tracks across different construction stages according to the area-restricted nature of construction activities. It then integrates generated interdependence into a network over time, to imply the cooperation patterns in stages and a task delivery across stages with a holistic view. To validate the approach, location data were collected from 31 workers working in a high-rise housing construction project for one week to construct the interdependence network of this project, which was used to quantitatively evaluate the performance of construction schedule, assignments and cooperation. Results show that the interdependence network is able to provide insightful information on how workers perform individual tasks onsite and it is also an effective tool to identify and display the interactions among site workers.
URI: http://hdl.handle.net/10397/74170
ISSN: 1474-0346
EISSN: 1474-0346
DOI: 10.1016/j.aei.2017.09.003
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

2
Last Week
0
Last month
Citations as of Mar 24, 2019

WEB OF SCIENCETM
Citations

2
Last Week
0
Last month
Citations as of Apr 8, 2019

Page view(s)

30
Last Week
0
Last month
Citations as of May 21, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.