Journal of Chaohu University ›› 2019, Vol. 21 ›› Issue (6): 116-126.doi: 10.12152/j.issn.1672-2868.2019.06.017
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Electronic Engineering Department, Wanjiang College of Anhui Normal University, Wuhu Anhui 241000
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Abstract: This paper proposes an indoor positioning study based on embedded platform and kNN algorithm, and locates the model in the experimental environment. First, the RFID (Radio Frequency Identification)reader collects RSSI (Received Signal Strength Indication)and sends the data to the embedded platform. After receiving the value,the kNN (k-Nearest Neighbor)algorithm is used to determine the target position, which can achieve higher accuracy positioning. The algorithm code uses Python language, and the hardware platform adopts ARM architecture. This method has the advantages of small size, simple code and convenient porting.
Key words: embedded platform, kNN, indoor positioning algorithm, Python
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ZHANG Hui, HE Qian. Indoor Positioning Research Based on Embedded Platform and kNN Algorithm[J].Journal of Chaohu University, 2019, 21(6): 116-126.
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URL: http://xb.chu.edu.cn/EN/10.12152/j.issn.1672-2868.2019.06.017
http://xb.chu.edu.cn/EN/Y2019/V21/I6/116
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