Paper Info
Title
Indoor Intelligent Fingerprint-Based Localization: Principles, Approaches and Challenges
Abstract
With the rapid development of Internet of Things (IoT) technology, location-based services have been widely applied in the construction of smart cities. Satellite-based location services have been utilized in outdoor environments, but they are not suitable for indoor technology due to the absence of global positioning system (GPS) signal. Therefore, many indoor localization technologies and systems have emerged by utilizing many other signals. In particular, fingerprinting localization has recently garnered attention because its promising performance. In this work, we aim to study recent indoor localization technologies and systems based on various fingerprints, which use machine learning and intelligent algorithms. We also present the architecture of intelligent localization. The development of indoor localization technology should have the ability of self-adaptation and self-learning in the future. And the architecture shows how to make localization become more “smart” by advanced techniques. The state-of-the-art localization systems' working principles are summarized and compared in terms of their localization accuracy, latency, energy consumption, complexity, and robustness. We also discuss the challenges of existing indoor localization technologies, potential solutions to these challenges, and possible improvement measures.
Year
DOI
Venue
2020
10.1109/COMST.2020.3014304
IEEE Communications Surveys & Tutorials
Keywords
DocType
Volume
Internet of Things,intelligent localization,fingerprint,machine learning
Journal
22
Issue
Citations 
PageRank 
4
7
0.46
References 
Authors
0
6
Name
Order
Citations
PageRank
xiaoqiang zhu117314.91
Wenyu Qu257666.94
Tie Qiu389580.18
Laiping Zhao4185.04
mohammed atiquzzaman51205124.47
Dapeng Wu64463325.77