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학술대회 Design of Aging-Resistant Wi-Fi Fingerprint-based Localization System with Continuous Active Learning
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저자
김영삼, 김수형
발행일
201802
출처
International Conference on Advanced Communications Technology (ICACT) 2018, pp.1054-1059
ISSN
2288-0003
DOI
https://dx.doi.org/10.23919/ICACT.2018.8323934
협약과제
17HH3600, 상황인지기반 멀티팩터 인증 및 전자서명을 제공하는 범용인증플랫폼기술 개발, 김수형
초록
Wi-Fi fingerprint-based localization systems are widely used for indoor localization as it only needs Wi-Fi network infrastructure that exists almost everywhere nowadays. However, it can be vulnerable to environmental change if Wi-Fi fingerprint-based localization system uses fixed Wi-Fi fingerprint database as training dataset and has no method for updating training dataset. In this paper, we propose AR-WFL system including update phase that can reflect environmental change periodically and prevent performance degradation. The proposed AR-WFL system is based on crowdsourcing and no dedicated annotator exists. In addition, we adopt active learning scheme with uncertainty selective sampling algorithm to maximize cost-efficiency of the update phase. We evaluate the performance of the update phase as location estimation accuracy using a dataset we collected for 2 months. It shows that average accuracy is increased by 1.83%p using update phase with uncertainty sampling algorithm compared with the system without an update phase.
키워드
Active learning, Database update, Indoor localization, Selective sampling, Wi-Fi fingerprint
KSP 제안 키워드
Cost Efficiency, Environmental change, Fingerprint database, Localization systems, Location estimation accuracy, Sampling algorithm, Uncertainty sampling, Wi-Fi network, WiFi fingerprint, active learning(AL), fingerprint-based localization