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Author: Oktem, RusenSubject: classification

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Now showing 1 - 2 of 2
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    Conference Object
    An Rfid Based Location Finding and Tracking With Guidance
    (Ieee, 2008) Oktem, Rusen; Aydin, Elif Uray; Cagiltay, Nergiz Ercil
    This paper tackles an RFID based location finding and tracking system. The system is an integral part of a navigation aid being developed for guiding visually disabled people in a store. The aid is composed of a portable hardware interface unit, a standalone RFID unit, and a central processing unit. The units interact via wireless communication to locate the position of the user in a known indoor environment and tracking his/her movement. An active RFID tag helps to estimate the location of a user and the user is guided to follow a route accordingly, via a tactile compass. The system uses RF signal strengths and is based on Bayes Decision Theory. Initial simulation results with the system prove promising for location finding and tracking, especially when the tracked person is guided by a system.
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    Article
    Citation - WoS: 10
    Citation - Scopus: 15
    An Rfid Based Indoor Tracking Method for Navigating Visually Impaired People
    (Tubitak Scientific & Technological Research Council Turkey, 2010) Oktem, Rusen; Aydin, Elif
    This paper tackles the RFID based tracking problem in an obscured indoor environment. The proposed solution is an integral part of a navigation aid for guiding visually impaired people in a store. It uses RF signal strengths and is based on the Bayes Decision Theory. An observation vector is formed by received radio signal strength indication values, transmitted from three transmitters at distinct frequencies in the UHF band. The indoor area is divided into square grids, where each grid is considered as a class. The problem of tracking is expressed as classifying the observed radio signal strengths to the most likely class. A classification rule is formulated by incorporating a priori assumptions appropriate for the studied model. The proposed approach is tested in a laboratory environment. The results prove that the proposed approach is promising in tracking especially when the tracked person is guided by a system.