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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
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.
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