과제정보
본 연구는 과학기술정보통신부 및 보통신기획평가원의 ICT명품인재양성 사업(IITP-2020-2051-001), Grand ICT연구센터지원사업(IITP-2020-2015-0-00742)과 2020년도 정부(교육과학기술부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2020R1A2C2008447).
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Discrete Wavelet Transform (DWT) is an effective technique that is commonly used for detecting noise in collected data of an individual sensor. In addition, the detection accuracy can be significant improved by exploiting the correlation in the data of neighboring sensors of Wireless Sensor Networks (WSNs). Principal component analysis is the powerful technique to analyze the correlation in the multivariate data. In this paper, we propose a DWT-PCA combination scheme for noise detection (DWT-PCA-ND). Experimental results on a real dataset show a remarkably higher performance of DWT-PCA-ND comparing to conventional PCA scheme in detection of noise that is a popular anomaly in collected data of WSN.
본 연구는 과학기술정보통신부 및 보통신기획평가원의 ICT명품인재양성 사업(IITP-2020-2051-001), Grand ICT연구센터지원사업(IITP-2020-2015-0-00742)과 2020년도 정부(교육과학기술부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2020R1A2C2008447).