Title: A 3D localisation method for searching survivors/corpses based on WSN and Kalman filter

Authors: Junbo Wang; Zixue Cheng; Taishi Yoshida; Yinghui Zhou; Lei Jing

Addresses: School of Computer Science and Engineering, University of Aizu, 965-8580, Japan ' School of Computer Science and Engineering, University of Aizu, 965-8580, Japan ' Graduate School of Computer Science and Engineering, University of Aizu, 965-8580, Japan ' Graduate School of Computer Science and Engineering, University of Aizu, 965-8580, Japan ' School of Computer Science and Engineering, University of Aizu, 965-8580, Japan

Abstract: Localisation is a key technique in Internet of Things (IoT) and wireless sensor network (WSN). Currently, for indoor localisation there are many approaches, e.g., RFID based, ultrasonic sensor based, etc. However, when an earthquake happens, the devices for localisation in a building may be damaged and how to quickly locate the survivors/corpses buried in a collapse regional is a key issue. In the paper, we propose a 3D localisation method for searching survivors/corpses based on WSN. It mainly consists of two stages. In the first stage, a draft location is calculated based on beacon nodes, and then a detailed location is computed in the second stage based on a mobile beacon node moving along a triangle. Meanwhile, we employed Kalman filter in the method to acquire stable received signal strength indicators (RSSIs). Finally, we implement a robot car with a sensor node acting as a mobile beacon node and evaluate the proposed method through experiments in a gym.

Keywords: IoT; internet of things; WSNs; wireless sensor networks; 3D localisation; mobile beacon nodes; Kalman filter; search for survivors; search for bodies; earthquakes; received signal strength indicators; RSSI; robot cars; mobile robots; emergency response; emergency management; earthquake survivors.

DOI: 10.1504/IJSNET.2015.072866

International Journal of Sensor Networks, 2015 Vol.19 No.3/4, pp.181 - 193

Available online: 05 Nov 2015 *

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