Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105684
Title: | A graph-based method for indoor subarea localization with zero-configuration | Authors: | Chen, Y Guo, M Shen, J Cao, J |
Issue Date: | 2016 | Source: | 2016 International IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), 18 - 21 July 2016, Toulouse, France, p. 236-244 | Abstract: | Indoor subarea localization remains an open problem due to existing studies face two main bottlenecks, one is fingerprint-based methods require time-consuming site survey, another is triangulation-based methods is lack of scalability in large-scale environment. In this paper, we aim to present a graph-based method for indoor subarea localization with zero-configuration, which can be directly employed without offline manually constructing fingerprint map or pre-installing additional infrastructure. To accomplish this, we first utilize two unexploited characteristics of WiFi radio signal strength to generate logical floor graph,, then formulate the problem of constructing fingerprint map in terms of a graph isomorphism problem between logical floor graph, physical floor graph. Then, a Bayesian-based approach is utilized to estimate the unknown subarea in online localization. The proposed method has been implemented in a real-world shopping mall, extensive experimental results show that our method can achieve competitive performance comparing with existing methods. | Publisher: | Institute of Electrical and Electronics Engineers | ISBN: | 978-1-5090-2771-2 (Electronic) 978-1-5090-2772-9 (Print on Demand(PoD)) |
DOI: | 10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054 | Rights: | ©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The following publication Y. Chen, M. Guo, J. Shen and J. Cao, "A Graph-Based Method for Indoor Subarea Localization with Zero-Configuration," 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), Toulouse, France, 2016, pp. 236-244 is available at https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0054. |
Appears in Collections: | Conference Paper |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Cao_Graph-Based_Method_Indoor.pdf | Pre-Published version | 1.38 MB | Adobe PDF | View/Open |
Page views
5
Citations as of Apr 28, 2024
SCOPUSTM
Citations
2
Citations as of Apr 26, 2024
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.