Indoor navigation systems based on data mining techniques in internet of things: a survey

被引：0
作者：
Mahbubeh Sattarian
Javad Rezazadeh
Reza Farahbakhsh
Alireza Bagheri
机构：
[1] Islamic Azad University,Tehran North Branch
[2] University of Technology Sydney,undefined
[3] Institut Mines-Telecom,undefined
[4] Telecom Sud-Paris,undefined
[5] Amirkabir University of Technology,undefined
来源：
Wireless Networks | 2019年 / 25卷
关键词：
IoT; Indoor navigation system; Indoor positioning; Data mining; Machine learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Internet of Things (IoT) is turning into an essential part of daily life, and numerous IoT-based scenarios will be seen in future of modern cities ranging from small indoor situations to huge outdoor environments. In this era, navigation continues to be a crucial element in both outdoor and indoor environments, and many solutions have been provided in both cases. On the other side, recent smart objects have produced a substantial amount of various data which demands sophisticated data mining solutions to cope with them. This paper presents a detailed review of previous studies on using data mining techniques in indoor navigation systems for the loT scenarios. We aim to understand what type of navigation problems exist in different IoT scenarios with a focus on indoor environments and later on we investigate how data mining solutions can provide solutions on those challenges.
引用
收藏
页码：1385 / 1402
页数：17
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