The Use of Support Vector Machines in Wi-Fi Based Indoor Localization Detection and the Effect of Kernel Function Selection on Classification Performance: An Example of Finding the Location of Kindergarten Students

Year 2022, , 1370 - 1382, 12.12.2022

Ebru Efeoğlu

https://doi.org/10.47495/okufbed.1057825

Abstract

In recent years, the importance of locating children indoors has increased due to the problems in child safety. In this study, the locations of children in different rooms were determined by using wireless signal strength and Support Vector Machines classification algorithm. In addition, the effects of the algorithm on the classification performance were examined using different kernel functions and cross-validation technique was used for performance analysis. In the performance analysis, Confusion matrix, Precision, Sensitivity, F-Score, AUC, Accuracy, Kappa statistical value and Root Mean Square Error value were examined. As a result of the analysis, when linear kernel functions are preferred, the highest performance metrics were obtained and 97.9% success was observed

Keywords

WiFi, Support vector machines, Kernel, Indoor localization

Destek Vektör Makinelerinin Wi-Fi Tabanlı İç Mekan Lokalizasyon Tespitinde Kullanımı ve Çekirdek Fonksiyon Seçiminin Sınıflandırma Performansına Etkisi

Abstract

Son yıllarda çocuk güvenliğinde yaşanan kazaların artması nedeniyle iç mekanlarda çocukların yerini tespit etme çalışmaları önem kazanmıştır. Bu çalışmada kablosuz sinyal gücü ve Destek Vektör Makineleri sınıflandırma algoritması kullanılarak iç mekanlarda farklı odalarda bulunan insanların konumları tespit edilmiştir. Algoritmanın performansının arttırılması için farklı çekirdek fonksiyonları denenmiş ve çekirdek fonksiyonu seçiminin algoritmanın sınıflandırma performansına etkisi incelenmiştir. Performans ölçüm yöntemi olarak 10 kat çapraz doğrulama yöntemi kullanılmıştır. Performans değerlendirmesi, çapraz doğrulama öncesi ve sonrası sınıflandırma performansları karşılaştırılarak yapılmıştır. Yapılan performans değerlendirmesi sonucu iç mekanda konum belirlemede Destek Vektör Makineleri algoritması kullanılırken doğrusal çekirdek fonksiyonunun seçimi uygun görülmüştür.

Keywords

Kablosuz Sinyal Gücü, Destek Vektör Makineleri, Çekirdek Fonksiyon, İç Mekan Konum Belirleme, WiFi, Support vector machines, Kernel, Indoor localization

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