Skip to main content
DORAS
DCU Online Research Access Service
Login (DCU Staff Only)
A comprehensive study of bluetooth fingerprinting-based algorithms for localization

Zhang, Li, Liu, Xiao, Song, Jie, Gurrin, Cathal ORCID: 0000-0003-4395-7702 and Zhu, Zhiliang (2013) A comprehensive study of bluetooth fingerprinting-based algorithms for localization. In: 2013 27th International Conference on Advanced Information Networking and Applications Workshops, 25-28 Mar 2013, Barcelona, Spain. ISBN 978-0-7695-4952-1

Full text available as:

[img]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
850kB

Abstract

There is an increasing demand for indoor navigation and localization systems along with the increasing popularity of location based services in recent years. According to past researches, Bluetooth is a promising technology for indoor wireless positioning due to its cost-effectiveness and easy-to-deploy feature. This paper studied three typical fingerprinting-based positioning algorithms - kNN, Neural Networks and SVM. According to our analysis and experimental results, the kNN regression method is proven to be a good candidate for localization in real-life application. Comprehensive performance comparisons including accuracy, precision and training time are presented.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Bluetooth indoor positioning; Fingerprinting; kNN; Neural Networks; SVM
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: WAINA '13: 27th International Conference on Advanced Information Networking and Applications Workshops. . IEEE. ISBN 978-0-7695-4952-1
Publisher:IEEE
Official URL:http://dx.doi.org/10.1109/WAINA.2013.205
Copyright Information:© 2013 IEEE
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:National Natural Science Foundation of China under Grant No. 61173028, Natural Science Foundation of Liaoning Province under Grant No.200102059, Fundamental Research Funds for the Central Universities N110417002
ID Code:25542
Deposited On:23 Feb 2021 11:57 by Michael Scriney . Last Modified 16 Dec 2022 10:41

Downloads

Downloads per month over past year

Archive Staff Only: edit this record

  • Student Email
  • Staff Email
  • Student Apps
  • Staff Apps
  • Loop
  • Disclaimer
  • Privacy
  • Contact Us