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Sensors 2018, 18(11), 3862; https://doi.org/10.3390/s18113862

BLocate: A Building Identification Scheme in GPS Denied Environments Using Smartphone Sensors

Information and Communication Engineering, Yeungnam University, Gyeongbuk, Gyeongsan 38541, Korea
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Received: 22 September 2018 / Revised: 7 November 2018 / Accepted: 8 November 2018 / Published: 9 November 2018
(This article belongs to the Section Physical Sensors)
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Abstract

Indoor localization systems assume that the user’s current building is known by the GPS (Global Positioning System). However, such assumptions do not hold true in GPS denied environments or where the GPS cannot determine the user’s definite location. We present a novel solution to identify the building where the user is present now. The proposed building identification method works on the pervasive magnetic field using a smartphone. The accelerometer data determines the user’s activity of being stationary or walking. An Artificial Neural Network is used to identify the user’s activities and it shows good results. The magnetometer data is used to identify the user’s current building using the fingerprinting approach. Contrary to a traditional fingerprinting approach which stores intensity values, we utilize the patterns formed by the magnetic field strength in the form of a Binary Grid (BG). The BG approach overcomes the limitation of Dynamic Time Warping (DTW) whose performance is degraded when the magnitude of the magnetic data is changed. The experiments are performed with Samsung Galaxy S8 for eight various buildings with different altitudes and number of floors in Yeungnam University, Korea. The results demonstrate that the proposed building identification method can potentially be deployed for building identification. The precision, UAR (Unweighted Average Recall), F score, and Cohen’s Kappa values are used to determine the performance of the proposed system. The proposed systems shows very promising results. The system operates without any aid from any infrastructure dependent technologies like GPS or WiFi. Furthermore, we performed many experiments to investigate the impact of isolated points data to build fingerprint database on system’s accuracy with 1 m and 2 m distance. Results illustrate that by trading off a minor accuracy, survey labor can be reduced by 50 percent. View Full-Text
Keywords: building identification; magnetic field; smartphone sensors; ANN; global positioning system; accelerometer building identification; magnetic field; smartphone sensors; ANN; global positioning system; accelerometer
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Ashraf, I.; Hur, S.; Park, Y. BLocate: A Building Identification Scheme in GPS Denied Environments Using Smartphone Sensors. Sensors 2018, 18, 3862.

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