You are not logged in.
Openly accessible

Wireless sensor networks for heritage object deformation detection and tracking algorithm

Xie,Z, Huang,G, Zarei,R, He,J, Zhang,Y and Ye,H 2014, Wireless sensor networks for heritage object deformation detection and tracking algorithm, Sensors, vol. 14, no. 11, pp. 20562-20588, doi: 10.3390/s141120562.

Attached Files
Name Description MIMEType Size Downloads
huang-wirelesssensornetworks-2014.pdf Published version application/pdf 1.86MB 42

Title Wireless sensor networks for heritage object deformation detection and tracking algorithm
Author(s) Xie,Z
Huang,G
Zarei,R
He,J
Zhang,Y
Ye,H
Journal name Sensors
Volume number 14
Issue number 11
Start page 20562
End page 20588
Publisher MDPI AG
Place of publication Basel, Switzerland
Publication date 2014
ISSN 1424-8220
Keyword(s) Deformation
Detection
Heritage object monitoring
Sensor networks
Tracking
Summary Deformation is the direct cause of heritage object collapse. It is significant to monitor and signal the early warnings of the deformation of heritage objects. However, traditional heritage object monitoring methods only roughly monitor a simple-shaped heritage object as a whole, but cannot monitor complicated heritage objects, which may have a large number of surfaces inside and outside. Wireless sensor networks, comprising many small-sized, low-cost, low-power intelligent sensor nodes, are more useful to detect the deformation of every small part of the heritage objects. Wireless sensor networks need an effective mechanism to reduce both the communication costs and energy consumption in order to monitor the heritage objects in real time. In this paper, we provide an effective heritage object deformation detection and tracking method using wireless sensor networks (EffeHDDT). In EffeHDDT, we discover a connected core set of sensor nodes to reduce the communication cost for transmitting and collecting the data of the sensor networks. Particularly, we propose a heritage object boundary detecting and tracking mechanism. Both theoretical analysis and experimental results demonstrate that our EffeHDDT method outperforms the existing methods in terms of network traffic and the precision of the deformation detection.
Language eng
DOI 10.3390/s141120562
Field of Research 080504 Ubiquitous Computing
Socio Economic Objective 810105 Intelligence
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, MDPI AG
Persistent URL http://hdl.handle.net/10536/DRO/DU:30070661

Document type: Journal Article
Collections: School of Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in TR Web of Science
Scopus Citation Count Cited 0 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 126 Abstract Views, 43 File Downloads  -  Detailed Statistics
Created: Fri, 13 Mar 2015, 10:48:19 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.