Performance Evaluations and Feature Vector by Implementing Hybrid Filter in BLE-Based Fingerprinting 


Vol. 44,  No. 8, pp. 1556-1565, Aug.  2019
10.7840/kics.2019.44.8.1556


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  Abstract

Recently, many researches on various location-based services that can be used in indoor space using smart phones have been increased. In this paper, we have implemented fingerprinting-based indoor positioning system and validated performance of KNN and Feature Vector Algorithm to improve the accuracy of the experiment of the fingerprinting technique, by constructing indoor testbed. Moreover, to increase the accuracy of RSSI from Beacon, we have implemented Hybrid Filter using Garbage Filter and Kalman Filter. Also, the performance of the filter has been evaluated by the results of experiment.

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  Cite this article

[IEEE Style]

T. Lee, J. Kim, D. Kim, J. Lee, "Performance Evaluations and Feature Vector by Implementing Hybrid Filter in BLE-Based Fingerprinting," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 8, pp. 1556-1565, 2019. DOI: 10.7840/kics.2019.44.8.1556.

[ACM Style]

Taewoo Lee, Jungwoo Kim, Deokyoo Kim, and Jaeho Lee. 2019. Performance Evaluations and Feature Vector by Implementing Hybrid Filter in BLE-Based Fingerprinting. The Journal of Korean Institute of Communications and Information Sciences, 44, 8, (2019), 1556-1565. DOI: 10.7840/kics.2019.44.8.1556.

[KICS Style]

Taewoo Lee, Jungwoo Kim, Deokyoo Kim, Jaeho Lee, "Performance Evaluations and Feature Vector by Implementing Hybrid Filter in BLE-Based Fingerprinting," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 8, pp. 1556-1565, 8. 2019. (https://doi.org/10.7840/kics.2019.44.8.1556)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880