Abstract
This paper presents a novel approach for mobile phone centric observation applied to indoor localization. The approach involves a localization fingerprinting methodology that takes advantage of the presence of magnetic field anomalies inside buildings, and uses all three components of the measured magnetic field vectors to improve accuracy. By using adequate soft computing techniques, it is possible to adequately balance the constraints of common solutions. The resulting system does not rely on any infrastructure devices and therefore is easy to manage and deploy. Experimental evaluations carried out in two different buildings confirm the satisfactory performance of indoor localization based on magnetic field vectors. These evaluations provided an error of (11.34 m, 4.78 m) in the (x, y) components of the estimated positions in the first building where experiments were carried out, with a standard deviation of (3.41 m, 4.68 m); and, in the second building, an error of (4 m, 2.98 m) with a deviation of (2.64 m, 2.33 m).
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This work has been sponsored by European Commission through the FP7-SOCIOTAL-609112 EU Project.
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Carrillo, D., Moreno, V., Skarmeta, A.F. (2015). MagicFinger: A New Approach to Indoor Localization. In: García-Chamizo, J., Fortino, G., Ochoa, S. (eds) Ubiquitous Computing and Ambient Intelligence. Sensing, Processing, and Using Environmental Information. UCAmI 2015. Lecture Notes in Computer Science(), vol 9454. Springer, Cham. https://doi.org/10.1007/978-3-319-26401-1_1
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DOI: https://doi.org/10.1007/978-3-319-26401-1_1
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