Calibration Cost Reduction of Indoor Localization Using Bluetooth Low Energy Beacon
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- As Mansur
- Department of Computer Science, Faculty of Mathematic and Natural Science, Universitas Negeri Medan
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- Shimizu Hiroshi
- Department of Human Intelligent Systems, Graduate School of Life Science and System Engineering, Kyushu Institute of Technology
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- Benaissa Brahim
- Department of Mechanical Systems Engineering, Toyota Technological Institute
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- Yoshida Kaori
- Department of Human Intelligent Systems, Graduate School of Life Science and System Engineering, Kyushu Institute of Technology
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- Köppen Mario
- Department of Creative Informatics, Graduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology
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説明
<p>Indoor localization based on Bluetooth low energy (BLE) beacons has been rapidly developed, and many approaches have been developed to achieve higher estimation accuracy. In these methods, the received signal strength (RSS) is the input. However, the measurement of indoor environments is affected easily; the signal may be reflected and attenuated by obstacles such as the human body, walls, and furniture, which creates a challenge for methods based on signal mapping. In this study, BLE signal characteristics are investigated in an indoor localization setting. An experiment is performed using one BLE beacon and multiple receivers installed at different wall and ceiling positions. The raw RSS is observed, and the relationship between the BLE beacon signal strength characteristics against the human body effect as well as the receiver’s placement in the observation area are discussed. Signal mapping is performed, where the signal strength is measured from all receivers simultaneously. The position estimation accuracy is examined based on different data scenarios. The results show that the estimation position estimated by the BLE beacon based on extensive BLE beacon data does not affect the estimation accuracy.</p>
収録刊行物
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- Journal of Advanced Computational Intelligence and Intelligent Informatics
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Journal of Advanced Computational Intelligence and Intelligent Informatics 26 (1), 97-106, 2022-01-20
富士技術出版株式会社
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詳細情報 詳細情報について
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- CRID
- 1390290791329427712
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- NII論文ID
- 130008142941
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- NII書誌ID
- AA12042502
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- ISSN
- 18838014
- 13430130
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- NDL書誌ID
- 031924969
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- 本文言語コード
- en
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- データソース種別
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- NDLサーチ
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