Hybrid wireless sensor network for rescue site monitoring after earthquake

Rui Wang; Shuo Wang; Chong Tang; Xiaoguang Zhao; Weijian Hu; Min Tan; Bowei Gao

doi:10.1117/1.JRS.10.036020

25 August 2016 Hybrid wireless sensor network for rescue site monitoring after earthquake

Rui Wang, Shuo Wang, Chong Tang, Xiaoguang Zhao, Weijian Hu, Min Tan, Bowei Gao

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 10, Issue 3, 036020 (August 2016). https://doi.org/10.1117/1.JRS.10.036020

Abstract

This paper addresses the design of a low-cost, low-complexity, and rapidly deployable wireless sensor network (WSN) for rescue site monitoring after earthquakes. The system structure of the hybrid WSN is described. Specifically, the proposed hybrid WSN consists of two kinds of wireless nodes, i.e., the monitor node and the sensor node. Then the mechanism and the system configuration of the wireless nodes are detailed. A transmission control protocol (TCP)-based request-response scheme is proposed to allow several monitor nodes to communicate with the monitoring center. UDP-based image transmission algorithms with fast recovery have been developed to meet the requirements of in-time delivery of on-site monitor images. In addition, the monitor node contains a ZigBee module that used to communicate with the sensor nodes, which are designed with small dimensions to monitor the environment by sensing different physical properties in narrow spaces. By building a WSN using these wireless nodes, the monitoring center can display real-time monitor images of the monitoring area and visualize all collected sensor data on geographic information systems. In the end, field experiments were performed at the Training Base of Emergency Seismic Rescue Troops of China and the experimental results demonstrate the feasibility and effectiveness of the monitor system.

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Rui Wang, Shuo Wang, Chong Tang, Xiaoguang Zhao, Weijian Hu, Min Tan, and Bowei Gao "Hybrid wireless sensor network for rescue site monitoring after earthquake," Journal of Applied Remote Sensing 10(3), 036020 (25 August 2016). https://doi.org/10.1117/1.JRS.10.036020

Published: 25 August 2016

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