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(to be completed)

 


ThinkMind // International Journal On Advances in Intelligent Systems, volume 2, number 4, 2009 // View article intsys_v2_n4_2009_5


Self-Organizing ZigBee Network and Bayesian Filter Based Patient Localization Approaches for Disaster Management

Authors:
Ashok-Kumar Chandra-Sekaran
Christophe Kunze

Keywords: Emergency response; ZigBee; self-configuration; patient localization; Bayesian filter based algorithms; close to reality simulation

Abstract:
A self-organizing, scalable, heterogeneous and location aware WSN architecture called Disaster Aid Network (DAN) for assisting the responders to provide efficient emergency response was proposed in our previous work. The two main aspects of DAN are the communication and localization aspect. As part of the DAN communication aspect, in this paper we have undergone empirical investigations to identify the suitability of ZigBee’s 2.4 GHz operation for DAN. A new self-configuring mechanism for patient data access by the doctor at the disaster site is also proposed. As part of the DAN localization aspect, in this paper we have implemented two new Bayesian filter based algorithms called Improved Range-Based Monte Carlo Patient Localization and Range- Based Unscented Kalman Filter Patient Localization for real time localization of large number of patients at the disaster site. The close-to-reality simulations of both these algorithms is done using a disaster management mobility model to identify their suitability for patient tracking. The new localization solution in tandem with the emergency response system shall facilitate efficient logistic support at the disaster site.

Pages: 446 to 456

Copyright: Copyright (c) to authors, 2009. Used with permission.

Publication date: March 17, 2010

Published in: journal

ISSN: 1942-2679

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