Multi-floor Positioning Method based on RSSI in Wireless Sensor Networks

Huizi Zhang, Hayato Fukunaga, Ryo Ishizuka, Tong Li, Shigeyuki Tateno

研究成果: Conference contribution

抄録

Recently, with the rapid development of wireless communication technologies, indoor positioning has been gradually applied to many occasions, such as positioning in complex multi-floor shopping malls. In the positioning of shopping malls, the Wi-Fi fingerprint positioning method is often used. Moreover, k-nearest neighbor algorithm is commonly used to estimate the position of the target point in some studies. However, the k-nearest neighbor algorithm searched in the database of the whole building, resulting in low accuracy of floor determination, large positioning errors, and large amount of calculation. To solve this problem, the database of a building should be reasonably divided into several clusters, and the clusters with the highest similarity to the target point should be used for positioning. Therefore, in this paper, a building fingerprint database clustering method based on signal distance and position distance is proposed. The results show that compared with the k-nearest neighbor algorithm, the floor determination accuracy is improved, and the positioning error is reduced.

本文言語English
ホスト出版物のタイトル2022 61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022
出版社Institute of Electrical and Electronics Engineers Inc.
ページ270-275
ページ数6
ISBN(電子版)9784907764784
DOI
出版ステータスPublished - 2022
イベント61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022 - Kumamoto, Japan
継続期間: 2022 9月 62022 9月 9

出版物シリーズ

名前2022 61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022

Conference

Conference61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022
国/地域Japan
CityKumamoto
Period22/9/622/9/9

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用
  • 制御およびシステム工学
  • 制御と最適化
  • 器械工学

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