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논문 기본 정보

저자정보
(Xi’an Jiaotong-Liverpool University) (Xi’an Jiaotong-Liverpool University) (Xi’an Jiaotong-Liverpool University)
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제어로봇시스템학회 제어로봇시스템학회 국제학술대회 논문집 ICCAS 2018
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    초록·키워드

    Key issues of indoor localization is taking full advantages and overcoming its disadvantages. Indoor localization based on Wi-Fi fingerprinting attracts researchers’ attentions since it does not require new infrastructure and devices. Many devices such as smart phones and laptops, which have a function to capture Wi-Fi signals, can be used for Wi-Fi fingerprinting. However, due to unreliable Wi-Fi signals, there are still difficulty to achieve high positioning accuracy. The unreliable signal disturbs devices to find their locations. As a result, getting localization with devices sometimes makes a wrong decision in building classification. It is useless for people to find a destination floor if they are in different building. In this paper, we propose two consecutive multi-layer perceptrons to get more precise localization. With sumple structure, we get better performance and show precise decision results in building classification, which is critical in Wi-Fi fingerprinting. We use UJIndoorLoc dataset which is open dataset.

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      UCI(KEPA) : I410-ECN-0101-2018-003-003538007