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Indoor positioning system based on an improved weighted-trilateration algorithm with fingerprinting technique

Title
Indoor positioning system based on an improved weighted-trilateration algorithm with fingerprinting technique
Authors
Choi H.Koo Y.Lee S.Park S.
Ewha Authors
박상수
SCOPUS Author ID
박상수scopus
Issue Date
2016
Journal Title
International Journal of Multimedia and Ubiquitous Engineering
ISSN
1975-0080JCR Link
Citation
International Journal of Multimedia and Ubiquitous Engineering vol. 11, no. 9, pp. 165 - 176
Keywords
FingerprintingiBeaconIndoor positioning systemLBSWeighted-trilateration algorithm
Publisher
Science and Engineering Research Support Society
Indexed
SCOPUS scopus
Document Type
Article
Abstract
Location Based Services (LBS) are software algorithm systems used by internet protocol capable wireless device technologies assist and/or replace Global Positioning System (GPS) with their task of acquiring and interpreting location describing data. LBS, and the data they provide, are increasingly being used by a growing number of users. As the demand for LBS grows, increasingly there is an additional requirement for more accurate indoor location position determination. Indoor localization algorithm has always been a challenge for location describing device manufacturers. This paper proposes a solution for improving accuracy while also decreasing computational requirements. Leveraging readily obtainable, cost-effective, Bluetooth Low Energy (BLE) Beacons, the research details a modified trilateration algorithm utilizing weighted nodes coupled with emitter/receiver distance measuring improvements accomplished using transmitter emission fingerprinting techniques. The proposed algorithm is evaluated through thorough experimentations that produce a reduction in difference between the real and measured location. The results found are solely obtained through algorithmic solutions utilizing standardized transmission protocols and readily available devices technologies. © 2016 SERSC.
DOI
10.14257/ijmue.2016.11.9.18
Appears in Collections:
인공지능대학 > 컴퓨터공학과 > Journal papers
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