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研究生(外文):Jui-Lun Chen
論文名稱(外文):A Passive RFID-based Access Control System for Nursing Homes
指導教授(外文):Rong-Shue Hsiao
口試委員(外文):Rong-Shue HsiaoSinn-Cheng LinHsin-Piao LinDing-Bing Lin
外文關鍵詞:RTLSpassive RFIDlocation fingerprintinggenetic algorithm
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人口老化是世界趨勢,目前許多養老機構面臨著照護人員和被照護者比例失衡問題,失智病患常尾隨著醫護人員或其他家屬離開養老院,發生人員走失的問題。因此須透過能辨識病患身分,並即時掌握其移動位置的門禁系統,方能防止問題發生。為建構此一門禁系統,本論文使用無線射頻辨識(radio frequency identification, RFID)裝置,同時滿足身分辨識和即時定位的需求;使用的被動式RFID擁有低價格、便於佈建與配戴,及維護成本低等優點。
本論文所提出之定位系統,是基於接收訊號強度(received signal strength, RSS)的訊號紋(fingerprinting)定位法。然而被動式RFID相較於主動式的無線技術,其RSS值在室內環境中,更易受到多路徑效應的影響而產生變動(fluctuation),進而影響定位效能。為促使RSS值的穩定並提升定位準確度,本論文使用基因演算法(genetic algorithm, GA)並結合電腦視覺(computer vision, CV)技術反饋現場的目標位置,藉由比較目標位置與無線定位結果所獲得的定位誤差,搜尋最適當的天線佈建位置,以改善RSS值變動問題,獲得最小的定位誤差,同時滿足即時定位的需求。
實驗結果顯示,本論文提出之定位系統可有效地辨識人員的身份與位置,在本論文的實驗情境中,身分辨識率可達100%,其區域辨識平均正確率為94.67%,平均定位誤差為0.15 m,而定位誤差在0.5 m以內時,精確度可達99 %以上。綜合上述結果,足見本系統可即時且準確的定位,符合應用之需求。
Population aging is a global trend; many nursing homes are facing the problem of unbalanced caregivers and patients. It is very often that dementia patients follow workers or other family members to leave the nursing home. To effectively solve this problem, it is needed to identify patients’ authority and know their location in real time. The thesis formulates the problem into a real-time localization problem. To build the real-time location system, radio frequency identification (RFID) devices are used to meet the real-time location and identification requirements. Moreover, passive RFID has advantages of low price, easily to wear and maintain.
The proposed location system adopts the received signal strength (RSS) based fingerprinting method. However, passive RFID suffers from RSS fluctuations due to multipath effects in indoor environments. The RSS fluctuations may reduce the performance of location system. In order to reduce RSS fluctuations and to improve the location accuracy, a sensor deployment method is presented. The proposed sensor deployment method integrates genetic algorithm (GA) with a computer vision (CV) system. The CV system provides actual location for the location system to estimate error distance of location. The error distance is fed back to GA algorithm to find the appropriate deployment locations for RFID reader antennas. The minimum location error and real-time requirement can be achieved.
The experimental results showed that the correct rate of the identification and area detection was 100% and 94.67%, respectively. The average error distance was within 0.15 m. For the location precision, the cumulative distribution function (CDF) of error distance of 0.5 m was 0.99. The performance can meet our requirement.
摘 要 i
誌 謝 v
目 錄 vi
表目錄 ix
圖目錄 x
第一章 緒論 1
1.1 前言 1
1.2 研究背景與動機 2
1.3 論文架構 9
第二章 相關研究 10
2.1 室內定位系統 10
2.2 無線鏈路RSS之研究 22
2.3 基於RSS的定位方法 24
2.4 基於RFID之定位系統 26
第三章 系統架構與研究方法 31
3.1 應用於門禁管制之定位系統 31
3.1.1 無線射頻辨識系統架構 31
3.1.2 門禁系統之定位機制 32
3.2 定位導向之佈建演算法 34
3.2.1 系統機制 34
3.2.2 族群初始化 36
3.2.3 基因演算法流程 39
3.2.4 佈建演算法和定位演算法之結合 43
3.3 混合式訊號紋定位演算法 44
3.3.1 系統機制 44
3.3.2 被動式RFID之RF鏈路特性 46
3.3.3 離線訓練階段 54
3.3.4 線上定位階段 58
第四章 實驗結果與分析 60
4.1 實驗環境與參數設置 60
4.1.1 實驗設備 60
4.1.2 天線之感測範圍 68
4.1.3 門禁管制系統實驗環境 70
4.2 系統效能評估指標 75
4.2.1 平均定位誤差 76
4.2.2 準確度累積分佈函數 76
4.3 實驗結果分析與比較 77
4.3.1 基因演算法挑選之天線組合結果 77
4.3.2 人員身分與區域辨識準確率結果及分析 82
4.3.3 門禁管制系統定位實驗結果及分析 83
4.3.4 門禁管制室內定位系統與其他方法效能之比較 89
第五章 結論與未來研究方向 92
5.1 結論 92
5.2 未來研究方向 93
參考文獻 94
附 錄 106
A. 發表之論文 107
B. 資料收集介面與定位計算程式 108
C. 實驗過程照片 109
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