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PINUS: Indoor Weighted Centroid Localization with Crowdsourced Calibration

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Parallel and Distributed Computing, Applications and Technologies (PDCAT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 931))

Abstract

PINUS, an indoor weighted centroid localization (WCL) method with crowdsourced calibration, is proposed in this paper. It relies on crowdsourcing to do the calibration for WCL to improve localization accuracy without the device diversity problem. Smartphones and Bluetooth Low Energy (BLE) beacon devices are applied to realize PINUS for the sake of design validation and performance evaluation.

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Acknowledgment

This work was supported in part by the Ministry of Science and Technology (MOST), Taiwan, under grant numbers 106-2218-E-008-003-, and 107-2918-I-008-002-. Special thanks go to Tokyo Metropolitan University, Japan, for providing international cooperation research opportunity in 2018.

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Authors and Affiliations

  1. National Central University, Taoyuan City, Taiwan

    Jehn-Ruey Jiang, Hanas Subakti & Ching-Chih Chen

  2. Tokyo Metropolitan University, Hachioji, Tokyo, Japan

    Kazuya Sakai

Authors
  1. Jehn-Ruey Jiang
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  2. Hanas Subakti
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  3. Ching-Chih Chen
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  4. Kazuya Sakai
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Corresponding author

Correspondence to Jehn-Ruey Jiang .

Editor information

Editors and Affiliations

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

    Jong Hyuk Park

  2. School of Computer Science, University of Adelaide, Adelaide, SA, Australia

    Hong Shen

  3. Department of Multimedia Engineering, Dongguk University, Seoul, Korea (Republic of)

    Yunsick Sung

  4. School of ICT, Griffith University, Gold Coast, Australia

    Hui Tian

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Jiang, JR., Subakti, H., Chen, CC., Sakai, K. (2019). PINUS: Indoor Weighted Centroid Localization with Crowdsourced Calibration. In: Park, J., Shen, H., Sung, Y., Tian, H. (eds) Parallel and Distributed Computing, Applications and Technologies. PDCAT 2018. Communications in Computer and Information Science, vol 931. Springer, Singapore. https://doi.org/10.1007/978-981-13-5907-1_46

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  • DOI: https://doi.org/10.1007/978-981-13-5907-1_46

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5906-4

  • Online ISBN: 978-981-13-5907-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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