Map-aware indoor area estimation with shortest path based on RSS fingerprinting

Heng Xiu Liu, Bo An Chen, Po Hsuan Tseng, Kai-Ten Feng, Tian Sheng Wang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

With the widespread of smartphones, people can easily figure out where they are and enjoy other advanced services like searching nearby restaurant information or checking bus arrival time. Indoor positioning becomes a popular issue for location- based services used in shopping malls, hospitals, or largescale buildings. Contrast with spacious surroundings of outdoor, indoor environment is filled with obstacles and moving people, which impose great challenges to provide precise estimation of indoor positioning. This paper proposes Wi-Fi fingerprinting technique using received signal strength with consideration of map information to effectively eliminate unreasonable estimation outcomes. The proposed area estimation (AE) algorithms calculate the similarity of each area in the entire region to increase accuracy of distinguishing which area the user locates. Moreover, the shortest path with adjacent recognition (SPAR) algorithm further utilizes the concept of Dijkstra's shortest path algorithm and the previous location information to predict user's position. Experimental results show that the proposed AE with SPAR algorithms can provide better area estimation compared to conventional scheme.

Original languageEnglish
Title of host publication2015 IEEE 81st Vehicular Technology Conference, VTC Spring 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479980888
DOIs
StatePublished - 1 Jul 2015
Event81st IEEE Vehicular Technology Conference, VTC Spring 2015 - Glasgow, United Kingdom
Duration: 11 May 201514 May 2015

Publication series

NameIEEE Vehicular Technology Conference
Volume2015
ISSN (Print)1550-2252

Conference

Conference81st IEEE Vehicular Technology Conference, VTC Spring 2015
CountryUnited Kingdom
CityGlasgow
Period11/05/1514/05/15

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  • Cite this

    Liu, H. X., Chen, B. A., Tseng, P. H., Feng, K-T., & Wang, T. S. (2015). Map-aware indoor area estimation with shortest path based on RSS fingerprinting. In 2015 IEEE 81st Vehicular Technology Conference, VTC Spring 2015 - Proceedings [7145926] (IEEE Vehicular Technology Conference; Vol. 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/VTCSpring.2015.7145926