Improved Indoor Localization System Using Statistical AP Selection Method Based on RSSI

Shigeyuki Tateno, Tong Li, Yu Wu, Ziyuan Wang

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

3 Citations (Scopus)

Abstract

Nowadays, the demand for nursing care service has been increasing rapidly with the growth of aging population and presence of chronic diseases. To ease the problem of workforce shortage in healthcare facilities, a novel remote monitoring system is proposed based on wireless communication. The developed system applied collected Received signal strength indicator (RSSI) for acquiring the position of patients and the elderly. Several methods based on RSSI are usually used like maximum likelihood estimation and trilateration. However, accuracies of these methods are not ideal for localization due to abnormal RSSI value caused by random reflection or refraction of radio propagation. In this paper, statistical AP selection method is applied to achieve distribution situation of trilateration results. Then Centroid and Kernel Density Estimation method are utilized to obtain estimation points according to distribution of combination. The experimental result shows that the localization system is sufficient with the improved strategy on positioning.

Original languageEnglish
Title of host publication2018 57th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1652-1657
Number of pages6
ISBN (Electronic)9784907764609
DOIs
Publication statusPublished - 2018 Oct 15
Event57th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2018 - Nara, Japan
Duration: 2018 Sept 112018 Sept 14

Other

Other57th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2018
Country/TerritoryJapan
CityNara
Period18/9/1118/9/14

Keywords

  • Exhaustion
  • Kernel Density Estimation
  • RSSI

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization
  • Instrumentation

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