Indoor Localization with Fingerprint Feature Extraction

Hanas Subakti, Hui Sung Liang, Jehn Ruey Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

We propose an indoor localization method using FPFE (Fingerprint Feature Extraction) with Bluetooth Low Energy (BLE) beacon fingerprints. FPFE apples either AE or PCA to extract features of beacon fingerprints and then measures the similarity between the features using the concept of the Minkowski distance. FPFE selects k RPs with the k smallest Minkowski distances for estimating the position of the target device. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that the FPFE achieves an average error of 0.68 m which is better than those of other related BLE fingerprint-based localization methods.

Original languageEnglish
Title of host publication2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages239-242
Number of pages4
ISBN (Electronic)9781728180601
DOIs
StatePublished - 23 Oct 2020
Event2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020 - Yunlin, Taiwan
Duration: 23 Oct 202025 Oct 2020

Publication series

Name2nd IEEE Eurasia Conference on IOT, Communication and Engineering 2020, ECICE 2020

Conference

Conference2nd IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2020
Country/TerritoryTaiwan
CityYunlin
Period23/10/2025/10/20

Keywords

  • Autoencoder
  • Bluetooth Beacon
  • Fingerprint Indoor Localization
  • Principal Component Analysis

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