Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Adaptive tracking and recording method for dynamic real-time WiFi fingerprint positioning

Authors
Liang Dong, Dong Liang
Corresponding Author
Liang Dong
Available Online January 2017.
DOI
10.2991/icmmita-16.2016.276How to use a DOI?
Keywords
WIFI; Fingerprint Positioning; Adaptive Tracking; Internet of Things; Algorithm
Abstract

The overall performance of fingerprint positioning system will be improved in this paper with the adoption of technology in artificial intelligence field and optimization technology. First, at offline stage, adaptive tracking and recording method for dynamic real-time WiFi fingerprint positioning has been proposed. Regional propagation model (RPM) of indoor wireless signal has been proposed through the RSS value clustering fading characteristics observed based indoor zoning principle in clustering channel modeling algorithm. Take samples from the reference points of sparse density distribution with adoption of affinity propagation clustering technology to attain fingerprints, and then divide the indoor area into sub regions with specific number, make use of the sampling data of each sub region to set up proposed RPM path loss propagation model and predict the fingerprints of other unmeasured reference points through this model to reconstruct complete fingerprint database. Experimental testing results have shown that the RSS prediction accuracy of proposed path loss propagation model is higher than existing propagation model; at the same time, when decrease fingerprint acquisition workload above 28%, the proposed algorithm can still attain high positioning accuracy.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
978-94-6252-285-5
ISSN
2352-538X
DOI
10.2991/icmmita-16.2016.276How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liang Dong
AU  - Dong Liang
PY  - 2017/01
DA  - 2017/01
TI  - Adaptive tracking and recording method for dynamic real-time WiFi fingerprint positioning
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 1197
EP  - 1202
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.276
DO  - 10.2991/icmmita-16.2016.276
ID  - Dong2017/01
ER  -