- 學位論文
以KNN演算法為基礎的Beacon裝置之室內定位研究
A Study of KNN Algorithm Based Indoor Positioning Using Beacon Devices
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摘要
隨著現代科技在資訊與通訊技術的蓬勃發展，適地性服務(Location Based Service, LBS)已經被廣泛的使用在各個層面，讓生活變得更智慧與便利。室內定位技術在LBS 中扮演一個重要的角色，以提供更多的服務應用。然而，在無線室內定位系統中，訊號在傳輸期間會被環境的雜訊所影響，因此為了降低干擾的問題與提高室內定位的準確度，在本文中，我們提出一個以Beacon 裝置為基礎且利用接收訊號強度指標(Received Signal Strength Indication, RSSI)的室內定位系統，並結合指紋定位方法，本研究以室內之空間，佈置9個位置作定位實驗，以卡爾曼濾波作訊號濾波，結合K個最近鄰(K-nearest neighbor, KNN)演算法研究。
並列摘要
With the rapid development of modern technology in information and communication technology, Location Based Services (LBS) have been widely used to make lives more intelligent and convenient. The indoor positioning technology plays an important role among LBS to provide more service applications. However, in wireless indoor positioning systems, signals are affected by environmental noises during the transmission. Therefore, to avoid the problem of interference and improve the accuracy of indoor positioning, in this paper, we propose a Beacon based on the indoor positioning system consisted of a fingerprint positioning method. This study uses the indoor space to arrange 9 locations for positioning experiments, uses the Kalman filter for signal filtering, and combines the K-nearest neighbor (KNN) algorithm.
參考文獻
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