@inproceedings{ba395341b5fb44c9ae1c51c0a8a73cc0,
title = "IoT-Aided Fingerprint Indoor Positioning Using Support Vector Classification",
abstract = "Wi-Fi based fingerprint indoor positioning technology is known as one of the most popular indoor positioning technologies. In this work, an internet of things (IoT) aided fingerprint indoor positioning system using support vector machine classifier has been proposed. The support vector classification with kernel tricks is introduced to accomplish multi-classes classification problem in fingerprint indoor positioning. Three kinds of kernel functions are investigated and compared based on results of the experiment performed in a real indoor environment. The results show support vector classifier with Gaussian RBF kernel function has highest positioning accuracy.",
keywords = "Fingerprint, Indoor positioning, IoT, Received Signal Strength, Support vector machine",
author = "Yiqiao Wei and Hwang, {Seung Hoon} and Lee, {Sang Moon}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 9th International Conference on Information and Communication Technology Convergence, ICTC 2018 ; Conference date: 17-10-2018 Through 19-10-2018",
year = "2018",
month = nov,
day = "16",
doi = "10.1109/ICTC.2018.8539594",
language = "English",
series = "9th International Conference on Information and Communication Technology Convergence: ICT Convergence Powered by Smart Intelligence, ICTC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "973--975",
booktitle = "9th International Conference on Information and Communication Technology Convergence",
address = "United States",
}