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Wi-Fi fingerprinting based on collaborative confidence level training

Jing, Hao; Pinchin, James; Hill, Chris; Moore, Terry

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Authors

Hao Jing

Chris Hill

Terry Moore



Abstract

Wi-Fi fingerprinting has been a popular indoor positioning technique with the advantage that infrastructures are readily available in most urban areas. However wireless signals are prone to fluctuation and noise, introducing errors in the final positioning result. This paper proposes a new fingerprint training method where a number of users train collaboratively and a confidence factor is generated for each fingerprint. Fingerprinting is carried out where potential fingerprints are extracted based on the confidence factor. Positioning accuracy improves by 40% when the new fingerprinting method is implemented and maximum error is reduced by 35%.

Citation

Jing, H., Pinchin, J., Hill, C., & Moore, T. (2016). Wi-Fi fingerprinting based on collaborative confidence level training. Pervasive and Mobile Computing, 30, https://doi.org/10.1016/j.pmcj.2015.10.005

Journal Article Type Article
Acceptance Date Oct 1, 2015
Online Publication Date Oct 22, 2015
Publication Date Aug 1, 2016
Deposit Date May 5, 2016
Publicly Available Date May 5, 2016
Journal Pervasive and Mobile Computing
Print ISSN 1574-1192
Electronic ISSN 1574-1192
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 30
DOI https://doi.org/10.1016/j.pmcj.2015.10.005
Keywords Indoor positioning; Wi-Fi fingerprinting; Collaborative positioning
Public URL https://nottingham-repository.worktribe.com/output/797610
Publisher URL http://dx.doi.org/10.1016/j.pmcj.2015.10.005

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