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MagicFinger: 3D Magnetic Fingerprints for Indoor Location

Given the indispensable role of mobile phones in everyday life, phone-centric sensing systems are ideal candidates for ubiquitous observation purposes. This paper presents a novel approach for mobile phone-centric observation applied to indoor location. The approach involves a location fingerprintin...

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Detalles Bibliográficos
Autores principales: Carrillo, Daniel, Moreno, Victoria, Úbeda, Benito, Skarmeta, Antonio F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4541928/
https://www.ncbi.nlm.nih.gov/pubmed/26184230
http://dx.doi.org/10.3390/s150717168
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author Carrillo, Daniel
Moreno, Victoria
Úbeda, Benito
Skarmeta, Antonio F.
author_facet Carrillo, Daniel
Moreno, Victoria
Úbeda, Benito
Skarmeta, Antonio F.
author_sort Carrillo, Daniel
collection PubMed
description Given the indispensable role of mobile phones in everyday life, phone-centric sensing systems are ideal candidates for ubiquitous observation purposes. This paper presents a novel approach for mobile phone-centric observation applied to indoor location. The approach involves a location fingerprinting methodology that takes advantage of the presence of magnetic field anomalies inside buildings. Unlike existing work on the subject, which uses the intensity of magnetic field for fingerprinting, our approach 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. The proposed system consists of two phases: the offline phase and the online phase. In the offline phase, magnetic field measurements are taken throughout the building, and 3D maps are generated. Then, during the online phase, the user's location is estimated through the best estimator for each zone of the building. Experimental evaluations carried out in two different buildings confirm the satisfactory performance of indoor location 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 the 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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spelling pubmed-45419282015-08-26 MagicFinger: 3D Magnetic Fingerprints for Indoor Location Carrillo, Daniel Moreno, Victoria Úbeda, Benito Skarmeta, Antonio F. Sensors (Basel) Article Given the indispensable role of mobile phones in everyday life, phone-centric sensing systems are ideal candidates for ubiquitous observation purposes. This paper presents a novel approach for mobile phone-centric observation applied to indoor location. The approach involves a location fingerprinting methodology that takes advantage of the presence of magnetic field anomalies inside buildings. Unlike existing work on the subject, which uses the intensity of magnetic field for fingerprinting, our approach 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. The proposed system consists of two phases: the offline phase and the online phase. In the offline phase, magnetic field measurements are taken throughout the building, and 3D maps are generated. Then, during the online phase, the user's location is estimated through the best estimator for each zone of the building. Experimental evaluations carried out in two different buildings confirm the satisfactory performance of indoor location 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 the 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). MDPI 2015-07-15 /pmc/articles/PMC4541928/ /pubmed/26184230 http://dx.doi.org/10.3390/s150717168 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Carrillo, Daniel
Moreno, Victoria
Úbeda, Benito
Skarmeta, Antonio F.
MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title_full MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title_fullStr MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title_full_unstemmed MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title_short MagicFinger: 3D Magnetic Fingerprints for Indoor Location
title_sort magicfinger: 3d magnetic fingerprints for indoor location
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4541928/
https://www.ncbi.nlm.nih.gov/pubmed/26184230
http://dx.doi.org/10.3390/s150717168
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