NDLI: Wi-Fi Fingerprint-Based Indoor Localization Method via Standard Particle Swarm Optimization

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Wi-Fi Fingerprint-Based Indoor Localization Method via Standard Particle Swarm Optimization

Content Provider	MDPI
Author	Zheng, Jin Li, Kailong Zhang, Xing
Copyright Year	2022
Description	With the continuous development and improvement in Internet-of-Things (IoT) technology, indoor localization has received considerable attention. Particularly, owing to its unique advantages, the Wi-Fi fingerprint-based indoor-localization method has been widely investigated. However, achieving high-accuracy localization remains a challenge. This study proposes an application of the standard particle swarm optimization algorithm to Wi-Fi fingerprint-based indoor localization, wherein a new two-panel fingerprint homogeneity model is adopted to characterize fingerprint similarity to achieve better performance. In addition, the performance of the localization method is experimentally verified. The proposed localization method outperforms conventional algorithms, with improvements in the localization accuracy of 15.32%, 15.91%, 32.38%, and 36.64%, compared to those of KNN, SVM, LR, and RF, respectively.
Starting Page	5051
e-ISSN	14248220
DOI	10.3390/s22135051
Journal	Sensors
Issue Number	13
Volume Number	22
Language	English
Publisher	MDPI
Publisher Date	2022-07-05
Access Restriction	Open
Subject Keyword	Sensors Industrial Engineering Wi-fi Fingerprint Indoor Localization Particle Swarm Optimization Location Estimation
Content Type	Text
Resource Type	Article

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