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An Indoor Positioning System Using RSSI and BSSID

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Advances in Computer Science and Ubiquitous Computing (CUTE 2017, CSA 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 474))

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Abstract

Research on indoor positioning technology has been carried out using various methods including WiFi, BLE, and terrestrial magnetism. The present proposes a system providing location information by collecting WiFi data (RSSI, BSSID). The proposed system applies an ensemble learning method of RandomForest to compare differentiation performance. RSSI and BSSID were used as differentiation performance variables, and the proposed indoor space was divided into grid shapes for the experiment. The algorithm presented in the experiment proves improved speed and accuracy compared to a RandomForest method that uses RSSI alone. The present study is expected to be utilized in the fields of indoor navigation and emergency rescue.

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References

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Acknowledgment

This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government MSIP (No. 2017008886).

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Authors and Affiliations

  1. Department of Computer Engineering, Hoseo University, 20, Hoseo-ro 79beon-gil, Baebang-eup, Asan-si, Chungcheongnam-do, 31499, Korea

    Sunmin Lee & Nammee Moon

Authors
  1. Sunmin Lee
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  2. Nammee Moon
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Corresponding author

Correspondence to Nammee Moon .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science and Technology, Seoul, Korea (Republic of)

    James J. Park

  2. Department of Business Science, University of Salerno, Salerno, Italy

    Vincenzo Loia

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Soul-t’ukpyolsi, Korea (Republic of)

    Gangman Yi

  4. Department of Multimedia Engineering, Dongguk University, Seoul, Soul-t’ukpyolsi, Korea (Republic of)

    Yunsick Sung

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Lee, S., Moon, N. (2018). An Indoor Positioning System Using RSSI and BSSID. In: Park, J., Loia, V., Yi, G., Sung, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2017 2017. Lecture Notes in Electrical Engineering, vol 474. Springer, Singapore. https://doi.org/10.1007/978-981-10-7605-3_165

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  • DOI: https://doi.org/10.1007/978-981-10-7605-3_165

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7604-6

  • Online ISBN: 978-981-10-7605-3

  • eBook Packages: EngineeringEngineering (R0)

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