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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

Distribution of the magnitude of the magnetic field along a corridor.
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f2-sensors-15-17168: Distribution of the magnitude of the magnetic field along a corridor.

Mentions: On this particular floor, several zones, such as a room with a large number of servers, computers, printers and lifts in different locations, are regarded as candidates for acting as magnetic field landmarks. Some of these locations are identified with dotted lines in Figure 1. The measurement system used to gather the data consists of an HTC One X phone equipped with a Hall-effect magnetometer, and the data acquisition frequency is 13 Hz. Samples are collected horizontally along a 50-m corridor by rotating a platform at each measurement point. The distance between each pair of measurement points is set to 150 cm. By analyzing the collected values for the magnetic field intensity (see Figure 2), a standard deviation of 7.6 μT and a difference of 55 μT between the maximum and the minimum of the magnetic field intensity is obtained. Therefore, we can assume that in a common building, such as a house, where the number of infrastructures installed would be lower, magnetic field variability alone would not be sufficient to achieve accurate position estimates.


MagicFinger: 3D Magnetic Fingerprints for Indoor Location.

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

Distribution of the magnitude of the magnetic field along a corridor.
© Copyright Policy
Related In: Results  -  Collection

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

f2-sensors-15-17168: Distribution of the magnitude of the magnetic field along a corridor.
Mentions: On this particular floor, several zones, such as a room with a large number of servers, computers, printers and lifts in different locations, are regarded as candidates for acting as magnetic field landmarks. Some of these locations are identified with dotted lines in Figure 1. The measurement system used to gather the data consists of an HTC One X phone equipped with a Hall-effect magnetometer, and the data acquisition frequency is 13 Hz. Samples are collected horizontally along a 50-m corridor by rotating a platform at each measurement point. The distance between each pair of measurement points is set to 150 cm. By analyzing the collected values for the magnetic field intensity (see Figure 2), a standard deviation of 7.6 μT and a difference of 55 μT between the maximum and the minimum of the magnetic field intensity is obtained. Therefore, we can assume that in a common building, such as a house, where the number of infrastructures installed would be lower, magnetic field variability alone would not be sufficient to achieve accurate position estimates.

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