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Abstract
The range of potential applications for indoor and campus based personnel localisation has led researchers to create a wide spectrum of different algorithmic approaches and systems. However, the majority of the proposed systems overlook the unique radio environment presented by the human body leading to systematic errors and inaccuracies when deployed in this context. In this paper RSSI-based Monte Carlo Localisation was implemented using commercial 868 MHz off the shelf hardware and empirical data was gathered across a relatively large number of scenarios within a single indoor office environment. This data showed that the body shadowing effect caused by the human body introduced path skew into location estimates. It was also shown that, by using two body-worn nodes in concert, the effect of body shadowing can be mitigated by averaging the estimated position of the two nodes worn on either side of the body.
Original language | English |
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Pages (from-to) | 173-184 |
Number of pages | 12 |
Journal | International Journal of Wireless Information Networks |
Volume | 19 |
Issue number | 3 |
DOIs | |
Publication status | Published - 01 Sept 2012 |
Bibliographical note
Copyright 2012 Elsevier B.V., All rights reserved.Fingerprint
Dive into the research topics of 'Empirical performance of RSSI-based Monte Carlo localisation for active RFID patient tracking systems'. Together they form a unique fingerprint.Projects
- 1 Finished
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R1118ECI: Centre for Secure Information Technologies (CSIT)
McCanny, J. V. (PI), Cowan, C. (CoI), Crookes, D. (CoI), Fusco, V. (CoI), Linton, D. (CoI), Liu, W. (CoI), Miller, P. (CoI), O'Neill, M. (CoI), Scanlon, W. (CoI) & Sezer, S. (CoI)
01/08/2009 → 30/06/2014
Project: Research