研究生: |
劉景文 Jing-Wen Liu |
---|---|
論文名稱: |
基於行人推算導航演算法與定位座標校正實現護理推車定位系統 A PDR-based Indoor Positioning System in a Nursing Cart with iBeacon-based Calibration |
指導教授: |
呂政修
Jenq-Shiou Leu |
口試委員: |
周承復
Cheng-Fu Chou 衛信文 Hsin-Wen Wei 王瑞堂 Ruei-Tang Wang |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電子工程系 Department of Electronic and Computer Engineering |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 64 |
中文關鍵詞: | 適地性服務 、室內定位系統 、護理推車 、行人推算導航演算法 、藍牙設備 、接收訊號強度 、嵌入式設備 、慣性測量單元 |
外文關鍵詞: | Location-Based Service (LBS), Indoor Positioning System (IPS), Nursing Cart, Pedestrian Dead Reckoning (PDR), iBeacon, Received Signal Strength Indicator (RSSI), Embedded Devices, Inertial Measurement Unit (IMU) |
相關次數: | 點閱:568 下載:0 |
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在適地性服務(Location-Based Service, LBS)中,定位扮演著重要的角色。全球定位系統(Global Positioning System, GPS)已經廣泛被應用於室外定位(Outdoor Positioning)。然而,在室內環境中訊號受到障礙物與建築物的屏蔽而衰減,使得室內定位(Indoor Positioning)無法透過全球定位系統來取得目前所在的位置。根據護理人員回報,在醫院中有許多醫療設備使用完畢後沒有歸位,導致換班的時候,常常需要花許多時間找尋設備,因此迫切的需要一輛具有室內定位系統(Indoor Positioning System, IPS)的護理推車(Nursing Cart),應用於定位護理人員與移動式醫療設備。
在這篇論文中,我們提出在護理推車上實現一個基於行人推算導航演算法(Pedestrian Dead Reckoning, PDR)的室內定位系統,包含透過接收端(擺放在護理推車上的電腦)接收到發送端(藍牙設備)的接收訊號強度(Received Signal Strength Indicator, RSSI)來校正定位座標的功能,並且可以在資源有限的嵌入式設備(Embedded Device)中實現。為了評估此系統,我們已經在室內環境中進行真實的實驗,並且針對系統進行測試與調整。除了測試環境、個體與硬體設備等影響因素以外,我們也比較藍牙設備(iBeacon)的建置數量對於定位精確度的影響。實驗結果顯示此定位方式的有效性。
Abstract—The Global Positioning System (GPS) is widely applied for outdoor positioning. However, GPS signals may degrade in an indoor environment. A nursing cart with a stable and accurate indoor positioning system inside is highly demanded in the hospital. The cart can be used for tracking the employees or positioning movable medical devices. In this paper, we propose a Pedestrian Dead Reckoning (PDR) -based indoor positioning system with iBeacon calibrations. The proposed system can be implemented in the resource-limited embedded device. To evaluate the property of the proposed system, real experiments under indoor environments have been conducted. The experimental results showed the effectiveness of the proposed approach. We also compared the impact of the number of iBeacons on positioning accuracy.
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