提出了一种基于嵌入式平台与kNN（k-Nearest Neighbour）算法的室内定位研究，对实验环境中的模型进行定位分析。首先，通过RFID （Radio Frequency Identification）阅读器采集RSSI（Received Signal StrengthIndication）并将数据发送到嵌入式平台,接收到数值后，利用kNN算法确定目标位置,能够实现较高精确度的定位。算法代码采用Python语言，硬件平台采用ARM构架，该方法具有体积小、代码简洁、方便移植等优点。

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.