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http://dx.doi.org/10.12812/ksms.2011.13.1.107

A Study on Measurement Error Reduction of Indoor and Outdoor Location Determination in Fingerprint Method  

Kwon, Dae-Woo (Department of Industrial Engineering, INHA University)
Lee, Doo-Yong (Department of Industrial Engineering, INHA University)
Song, Young-Keun (Department of Industrial Engineering, INHA University)
Jang, Jung-Hwan (Department of Industrial Engineering, INHA University)
Lee, Chang-Ho (Department of Industrial Engineering, INHA University)
Publication Information
Journal of the Korea Safety Management & Science / v.13, no.1, 2011 , pp. 107-114 More about this Journal
Abstract
Location-Based Service(LBS) is a service that provides a variety of convenience in life using location information that can be obtained by mobile communication network or satellite signal. In order to provide LBS precisely and efficiently, we need the location determination technology, platform technology and server technology. In this study, we studied on how we can reduce the error on location determination of objects such people and things. Fingerprint location determination method was applied to this study because it can be used at current wireless communication infrastructure and less influenced by a variety of noisy environment than other location determination methods. We converted the probability value to logarithmic scale value because using the sum of k probability values is not suitable to be applied to weight determination. In order to confirm the performance of suggested method, we developed location determination test program with Visual Basic 6.0 and performed the test. According to indoor and outdoor test results, the suggested stochastic method reduced the distance error by 17%, 18% and 9% respectively at indoor environment and 25%, 11% and 4% at outdoor environment compared with deterministic NN, kNN and kWNN fingerprint methods.
Keywords
Location Based Service; Fingerprint; Error Reduction; Location Determination;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
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