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

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publication2022 61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages270-275
Number of pages6
ISBN (Electronic)9784907764784
DOIs
Publication statusPublished - 2022
Event61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022 - Kumamoto, Japan
Duration: 2022 Sep 62022 Sep 9

Publication series

Name2022 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
Country/TerritoryJapan
CityKumamoto
Period22/9/622/9/9

Keywords

  • Wi-Fi fingerprint positioning
  • clustering based on signal distance and position distance
  • multi-floor positioning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering
  • Control and Optimization
  • Instrumentation

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