Accurate WiFi based indoor positioning with continuous location sampling
J.E. van Engelen, J.J. van Lier, F.W. Takes, H. Trautmann, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), Springer, Dublin, Ireland, 2018, pp. 524–540.
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Conference Paper
| English
Author
van Engelen, J.E.;
van Lier, J.J.;
Takes, F.W.;
Trautmann, HeikeLibreCat 
Abstract
The ubiquity of WiFi access points and the sharp increase in WiFi-enabled devices carried by humans have paved the way for WiFi-based indoor positioning and location analysis. Locating people in indoor environments has numerous applications in robotics, crowd control, indoor facility optimization, and automated environment mapping. However, existing WiFi-based positioning systems suffer from two major problems: (1) their accuracy and precision is limited due to inherent noise induced by indoor obstacles, and (2) they only occasionally provide location estimates, namely when a WiFi-equipped device emits a signal. To mitigate these two issues, we propose a novel Gaussian process (GP) model for WiFi signal strength measurements. It allows for simultaneous smoothing (increasing accuracy and precision of estimators) and interpolation (enabling continuous sampling of location estimates). Furthermore, simple and efficient smoothing methods for location estimates are introduced to improve localization performance in real-time settings. Experiments are conducted on two data sets from a large real-world commercial indoor retail environment. Results demonstrate that our approach provides significant improvements in terms of precision and accuracy with respect to unfiltered data. Ultimately, the GP model realizes continuous location sampling with consistently high quality location estimates.
Publishing Year
Proceedings Title
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)
Page
524–540
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Cite this
van Engelen JE, van Lier JJ, Takes FW, Trautmann H. Accurate WiFi based indoor positioning with continuous location sampling. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD). Springer; 2018:524–540.
van Engelen, J. E., van Lier, J. J., Takes, F. W., & Trautmann, H. (2018). Accurate WiFi based indoor positioning with continuous location sampling. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), 524–540.
@inproceedings{van Engelen_van Lier_Takes_Trautmann_2018, place={Dublin, Ireland}, title={Accurate WiFi based indoor positioning with continuous location sampling}, booktitle={Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)}, publisher={Springer}, author={van Engelen, J.E. and van Lier, J.J. and Takes, F.W. and Trautmann, Heike}, year={2018}, pages={524–540} }
Engelen, J.E. van, J.J. van Lier, F.W. Takes, and Heike Trautmann. “Accurate WiFi Based Indoor Positioning with Continuous Location Sampling.” In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), 524–540. Dublin, Ireland: Springer, 2018.
J. E. van Engelen, J. J. van Lier, F. W. Takes, and H. Trautmann, “Accurate WiFi based indoor positioning with continuous location sampling,” in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), 2018, pp. 524–540.
van Engelen, J. E., et al. “Accurate WiFi Based Indoor Positioning with Continuous Location Sampling.” Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), Springer, 2018, pp. 524–540.
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