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MagicFinger: 3D Magnetic Fingerprints for Indoor Location.

Carrillo D, Moreno V, Úbeda B, Skarmeta AF - Sensors (Basel) (2015)

Bottom Line: 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 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).

View Article: PubMed Central - PubMed

Affiliation: Department of Information and Communications Engineering, University of Murcia, 30100 Murcia, Spain. daniel.carrillo2@um.es.

ABSTRACT
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).

No MeSH data available.


Related in: MedlinePlus

Magnetic field profiles of the corridor.
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f3-sensors-15-17168: Magnetic field profiles of the corridor.

Mentions: Because of this restriction, the variability existing in the values of the three components of the magnetic field is analyzed. Figure 3 shows the distribution of the magnetic field for each component. As can be seen, the mean of component z depends on the location in the corridor. Components x and y have a similar mean due to the rotation of the platform. This is because the coordinate system of the sensor is defined relative to the device's screen. Nevertheless, it is interesting that each measurement point has a different range of values for these two components. From these profiles, it can be seen that a more complete characterization of the building can be provided if each point is represented by the three components of the magnetic field sensed at that point. A similar conclusion was reached in [12], in which the authors showed how the magnetic field vector formed by the three components of the magnetic field measured during an experiment traced non-overlapping curves in the space, which means magnetic vectors can be considered sufficiently informative to prevent any ambiguity when location is being estimated.


MagicFinger: 3D Magnetic Fingerprints for Indoor Location.

Carrillo D, Moreno V, Úbeda B, Skarmeta AF - Sensors (Basel) (2015)

Magnetic field profiles of the corridor.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541928&req=5

f3-sensors-15-17168: Magnetic field profiles of the corridor.
Mentions: Because of this restriction, the variability existing in the values of the three components of the magnetic field is analyzed. Figure 3 shows the distribution of the magnetic field for each component. As can be seen, the mean of component z depends on the location in the corridor. Components x and y have a similar mean due to the rotation of the platform. This is because the coordinate system of the sensor is defined relative to the device's screen. Nevertheless, it is interesting that each measurement point has a different range of values for these two components. From these profiles, it can be seen that a more complete characterization of the building can be provided if each point is represented by the three components of the magnetic field sensed at that point. A similar conclusion was reached in [12], in which the authors showed how the magnetic field vector formed by the three components of the magnetic field measured during an experiment traced non-overlapping curves in the space, which means magnetic vectors can be considered sufficiently informative to prevent any ambiguity when location is being estimated.

Bottom Line: 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 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).

View Article: PubMed Central - PubMed

Affiliation: Department of Information and Communications Engineering, University of Murcia, 30100 Murcia, Spain. daniel.carrillo2@um.es.

ABSTRACT
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).

No MeSH data available.


Related in: MedlinePlus