Wireless Sensor Networks for Heritage Object Deformation Detection and Tracking Algorithm

被引:3
作者
Xie, Zhijun [1 ]
Huang, Guangyan [2 ]
Zarei, Roozbeh [3 ]
He, Jing [3 ]
Zhang, Yanchun [3 ]
Ye, Hongwu [4 ]
机构
[1] Ningbo Univ, Dept Informat Sci & Engn, Ningbo 315021, Zhejiang, Peoples R China
[2] Deakin Univ, Sch Informat Technol, Melbourne, Vic 3125, Australia
[3] Victoria Univ, Coll Engn & Sci, Melbourne, Vic 3011, Australia
[4] Zhejiang Fash Inst Technol, Hangzhou 315021, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
sensor networks; heritage object monitoring; deformation; detection and tracking; TARGET TRACKING; LOCALIZATION;
D O I
10.3390/s141120562
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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.
引用
收藏
页码:20562 / 20588
页数:27
相关论文
共 38 条
[1]  
[Anonymous], J SOFTW
[2]   Distributed and collaborative tracking for energy-constrained ad-hoc wireless sensor networks [J].
Balasubramanian, S ;
Elangovan, I ;
Jayaweera, SK ;
Namuduri, KR .
2004 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, VOLS 1-4: BROADBAND WIRELESS - THE TIME IS NOW, 2004, :1732-1737
[3]  
Ceriotti M, 2009, 2009 INTERNATIONAL CONFERENCE ON INFORMATION PROCESSING IN SENSOR NETWORKS (IPSN 2009), P277
[4]   CODA: A Continuous Object Detection and tracking Algorithm for wireless ad hoc sensor networks [J].
Chang, Wang-Rong ;
Lin, Hui-Tang ;
Cheng, Zong-Zhi .
2008 5TH IEEE CONSUMER COMMUNICATIONS AND NETWORKING CONFERENCE, VOLS 1-3, 2008, :168-+
[5]   A Single Mobile Target Tracking in Voronoi-based Clustered Wireless Sensor Network [J].
Chen, Jiehui ;
Salim, Mariam B. ;
Matsumoto, Mitsuji .
JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2011, 7 (01) :17-28
[6]   Dynamic clustering for acoustic target tracking in wireless sensor networks [J].
Chen, WP ;
Hou, JC ;
Sha, L .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2004, 3 (03) :258-271
[7]  
de Brito Lina M. Pestana, 2008, Fourth International Conference on Wireless and Mobile Communications. ICWMC 2008, P364, DOI 10.1109/ICWMC.2008.12
[8]  
Eddy W. F., 1977, ACM Transactions on Mathematical Software, V3, P398, DOI 10.1145/355759.355766
[9]  
Fu Y., 2010, J COMPUT RES DEV, V7, P251
[10]   NOVEL-APPROACH TO NONLINEAR NON-GAUSSIAN BAYESIAN STATE ESTIMATION [J].
GORDON, NJ ;
SALMOND, DJ ;
SMITH, AFM .
IEE PROCEEDINGS-F RADAR AND SIGNAL PROCESSING, 1993, 140 (02) :107-113