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RSSI based Proximity User Detection System using Exponential Moving Average  

Yun, Gi-Hun (Department of Electronics Engineering, Dongguk University)
Kim, Keon-Wook (Department of Electronics Engineering, Dongguk University)
Choi, Jae-Hun (Electronics and Telecommunications Research Institute)
Park, Soo-Jun (Electronics and Telecommunications Research Institute)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.47, no.4, 2010 , pp. 105-111 More about this Journal
Abstract
This paper proposes the recursive algorithm for passive proximity detection system based on signal strength. The system is designed to be used in the smart medicine chest in order to provide location-based service for the senior personnel. Due to the system profile, single receiver and uni-direction communication are applied over the signal attenuation model for the determination of user existence within certain proximity. The performance of conventional methods is subjective to the sight between the transmitter and receiver unless the direction of target is known. To appreciate the temporal and spatial locality of human subjects, the authors present exponential moving average (EMA) to compensate the unexpected position error from the direction and/or environment. By using optimal parameter, the experiments with EMA algorithm demonstrates 32.26% (maximum 40.80%) reduction in average of the error probability with 50% of consecutive sight in time.
Keywords
Detection; Proximity; RSSI; EMA; ROC;
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