A Two-Nearest Wireless Access Point-Based Fingerprint Clustering Algorithm for Improved Indoor Wireless Localization

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F23%3A50020752" target="_blank" >RIV/62690094:18450/23:50020752 - isvavai.cz</a>

Result on the web

<a href="https://www.ijournalse.org/index.php/ESJ/article/view/1854" target="_blank" >https://www.ijournalse.org/index.php/ESJ/article/view/1854</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.28991/ESJ-2023-07-05-019" target="_blank" >10.28991/ESJ-2023-07-05-019</a>

Result language

angličtina

Original language name

A Two-Nearest Wireless Access Point-Based Fingerprint Clustering Algorithm for Improved Indoor Wireless Localization

Original language description

Fingerprint database clustering is one of the methods used to reduce localization time and improve localization accuracy in a fingerprint-based localization system. However, optimal selection of initial hyperparameters, higher computation complexity, and interpretation difficulty are among the performance-limiting factors of these clustering algorithms. This paper aims to improve localization time and accuracy by proposing a clustering algorithm that is extremely efficient and accurate at clustering fingerprint databases without requiring the selection of optimal initial hyperparameters, is computationally light, and is easily interpreted. The two closest wireless access points (APs) to the reference location where the fingerprint is generated, as well as the labels of the two APs in vector form, are used by the proposed algorithm to cluster fingerprints. The simulation result shows that the proposed clustering algorithm has a localization time that is at least 45% faster and a localization accuracy that is at least 25% higher than the k-means, fuzzy c-means, and lightweight maximum received signal strength clustering algorithms. The findings of this paper further demonstrate the real-time applicability of the proposed clustering algorithm in the context of indoor wireless localization as low localization time and higher localization accuracy are the main objectives of any localization system.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Emerging Science Journal

ISSN

2610-9182

e-ISSN

2610-9182

Volume of the periodical

7

Issue of the periodical within the volume

5

Country of publishing house

IT - ITALY

Number of pages

9

Pages from-to

1762-1770

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85174955700