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JDR Vol.10 No.4 pp. 655-666
(2015)
doi: 10.20965/jdr.2015.p0655

Paper:

Analysis of Radio Wave Propagation in an Urban Environment and its Application to Initial Disaster Response Support

Youhei Kawamura*1, Hyongdoo Jang*2, Markus Wagner*3, Hajime Nobuhara*1, Ashraf M. Dewan*4, Bert Veenendaal*4, and Itaru Kitahara*1

*1Faculty of Engineering, Information and Systems, University of Tsukuba
1-1-1 Tenoudai, Tsukuba, Ibaraki 305-8573, Japan

*2Department of Mining Engineering, Curtin University, Kalgoorlie, Australia

*3School of Computer Science, University of Adelaide, Adelaide, Australia

*4Department of Spatial Sciences, Curtin University, Perth, Australia

Received:
February 2, 2015
Accepted:
April 28, 2015
Published:
August 1, 2015
Keywords:
emergency response, GIS, ZigBee, propagation, optimization
Abstract

When disasters strike, it is important to quickly collect and analyze disaster-related information immediately after the event. We have suggested ZigBee and geographic information systems (GIS) technologies to resolve these problems and provide an effective communications system. In this paper, a method for the rapid setup of short-range wireless networks infrastructure, which estimates the radio wave propagation and optimizes the positions of transmitters is proposed. Our estimation method is experimentally verified, and it combines ray-tracing with preliminarily obtained statistical attenuation information, which allows us to consider different types of the land and its elevation. Thus, we can determine the effective ranges for radio communication for each potential location in the actual environment. This information is then used in our optimization procedure to reduce the number of transmitters needed to establish connections.

Cite this article as:
Y. Kawamura, H. Jang, M. Wagner, H. Nobuhara, A. Dewan, B. Veenendaal, and I. Kitahara, “Analysis of Radio Wave Propagation in an Urban Environment and its Application to Initial Disaster Response Support,” J. Disaster Res., Vol.10, No.4, pp. 655-666, 2015.
Data files:
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Last updated on Oct. 19, 2019