A 3D localisation method for searching survivors/corpses based on WSN and Kalman filter. (2015)

• Record Type: Journal Article
• Authors: Wang, Junbo; Cheng, Zixue; Yoshida, Taishi; Zhou, Yinghui; Jing, Lei
• Is Part Of: International journal of sensor networks. Volume 19:Number 3/4(2015)
• Page Start: 181
• Page End: 193
• Publication Date: 2015
• Subjects: 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; Sensor networks -- Periodicals; 681.2
• Languages: English
• ISSNs: 1748-1279

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.