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Empirical Performance of RSSI-Based Monte Carlo Localisation for Active RFID Patient Tracking Systems

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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.

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Notes

  1. http://www.act-wireless.com

  2. http://www.ti.com/product/cc1110f32

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Acknowledgments

This work was supported in part by a research studentship from the Centre for Secure Information Technology, Institute of Electronics, Communications and Information Technology, Queen’s University Belfast. The author’s are grateful to ACT Wireless Limited for supplying equipment and data acquisition software, and are grateful to Dr. Adrian McKernan of ACT Wireless who assisted with the measurements.

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Authors and Affiliations

  1. The Institute of Electronics, Communications and Information Technology, Queen’s University Belfast, NI Science Park, Queen’s Road, Queen’s Island, Belfast, BT3 9DT, UK

    William P. L. Cully, Simon L. Cotton & William G. Scanlon

  2. Telecommunication Engineering, University of Twente, 7500 AE, Enschede, The Netherlands

    William G. Scanlon

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  1. William P. L. Cully
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  2. Simon L. Cotton
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  3. William G. Scanlon
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Correspondence to William G. Scanlon.

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Cully, W.P.L., Cotton, S.L. & Scanlon, W.G. Empirical Performance of RSSI-Based Monte Carlo Localisation for Active RFID Patient Tracking Systems. Int J Wireless Inf Networks 19, 173–184 (2012). https://doi.org/10.1007/s10776-012-0189-x

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