Comprehensive Analysis of Applied Machine Learning in Indoor Positioning Based on Wi-Fi: An Extended Systematic Review

被引:14
|
作者
Bellavista-Parent, Vladimir [1 ]
Torres-Sospedra, Joaquin [2 ]
Perez-Navarro, Antoni [1 ]
机构
[1] Univ Oberta Catalunya, Fac Comp Sci Multimedia & Telecommun, Barcelona 08018, Spain
[2] Univ Minho, Algoritmi Res Ctr CALG, P-4800058 Guimaraes, Portugal
关键词
indoor; positioning; Wi-Fi; bluetooth; Wi-Fi radio map; machine learning; NEURAL-NETWORK; LOCALIZATION; ALGORITHM; HYBRID;
D O I
10.3390/s22124622
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Nowadays, there are a multitude of solutions for indoor positioning, as opposed to standards for outdoor positioning such as GPS. Among the different existing studies on indoor positioning, the use of Wi-Fi signals together with Machine Learning algorithms is one of the most important, as it takes advantage of the current deployment of Wi-Fi networks and the increase in the computing power of computers. Thanks to this, the number of articles published in recent years has been increasing. This fact makes a review necessary in order to understand the current state of this field and to classify different parameters that are very useful for future studies. What are the most widely used machine learning techniques? In what situations have they been tested? How accurate are they? Have datasets been properly used? What type of Wi-Fi signals have been used? These and other questions are answered in this analysis, in which 119 papers are analyzed in depth following PRISMA guidelines.
引用
收藏
页数:25
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