臺灣博碩士論文加值系統

無線射頻辨識技術 ( Radio Frequency IDentification, RFID )，受到產業界與學術界的廣泛討論，其相關技術應用因此而蓬勃發展，同時更被視為提升未來生活作業效率的重要技術之一。而相關的應用中，RFID應用於室內位置定位上也逐漸受到重視與討論。在室內位置感知上，許多學者提出利用多種不同技術去執行室內定位系統的研究，而本研究旨在利用RFID技術於室內位置感知，並將此系統應用於居家照顧上與醫療院設備的管理和人員的監控。本研究是利用接收訊號強度法( Received Signal Strength, RSS )收集預先佈置的參考標籤的訊號強弱，並利用此訊號強弱設定Power Level的區域範圍，在追蹤未知物件時，將參考標籤的訊號資料和未知的追蹤標籤的訊號資料做比對後，利用模糊理論找出鄰近參考點後再以參考標籤的座標值取出算數平均數，藉此獲得未知標籤的座標。經由實驗證明，我們所提出的定位方法，能比LANDMARC方法更精準且更穩定的完成室內定位辨識。

In recent years, there has dramatic proliferation of research concerned with Radio Frequency Identification (RFID). The RFID technologies are getting considerable attentions not only from academic research but also from the applications of enterprise. One of most important issues of applications, prevailing throughout the last few decades of RFID application research is the indoor position location. Many researchers have used varied technologies to perform the object of indoor position location tracking. In our research, we will purpose a new method using RFID tags to perform indoor position location tracking. This method uses Received Signal Strength (RSS) to collect signal strength from reference tags beforehand, and then using signal strength to set up Power Level areas of ranges by reference tags. Next, using signal strength from reference tag to match signal strength by track tags. Finally, when track tags is set up into indoor environments, it will find out the position of neighboring reference tags by fuzzy set theory, and using arithmetic mean to make a calculation of the position location values, by this method to Figure down track tags position location. We conduct experiment to prove our methodology can provide a better accuracy than LANDMARC system.

Table of Contents
中文摘要 III
ABSTRACT II
TABLE OF CONTENTS III
LIST OF FIGURES V
LIST OF TABLES VI
1. INTRODUCTION 1
1.1 BACKGROUND AND MOTIVATION 1
1.2 OBJECTIVE 2
1.3 THE FRAMEWORK OF THESIS 3
2. LITERATURE REVIEW 4
2.1 A REVIEW OF RELEVANT POSITION TECHNOLOGY 4
2.1.1 Infrared 4
2.1.2 Ultrasonic 5
2.1.3 IEEE 802.11 5
2.1.4 Sensor 6
2.1.5 Radio Frequency Identification (RFID) 7
2.2 LANDMARC 8
2.3 THE METHOD OF MEASURING DISTANCE 13
2.3.1 Received Signal Strength (RSS) 14
2.4 THE CONCEPT OF POWEL LEVEL 15
2.5 FUZZY SET THEORY 18
2.5.1 Fuzzy Set 18
2.5.2 The concept of α-Cut 19
3. RESEARCH METHODOLOGY 20
3.1 PROCEDURE OF RESEARCH 20
3.2 THE LEARNING PHASE 21
3.3 THE LOCATING PHASE 26
3.4 GIVE AN EXAMPLE 32
4. EXPERIMENT 36
4.1 DEVICE OF EXPERIMENT 37
4.2 FRAMEWORK OF THE EXPERIMENT 38
4.4 RESULT OF PRIMARY EXPERIMENT 42
4.5 RESULT OF EXPERIMENT JOIN FUZZY 43
5. CONCLUSIONS AND FUTURE WORK 46
REFERENCE 47

List of Figures

Figure 1The system framework of LANDMARC 9
Figure 2 The workflow of the LANDMARC 12
Figure 3 The workflow of the location identification 20
Figure 4 The readers and tags in the testing environment 22
Figure 5 The reader’s range of Powel Level concept 23
Figure 6 The diagrammatic drawing of ALS decision 24
Figure 7 The diagrammatic drawing is signal strength of reference tags 25
Figure 8 Procedure of locating phase 27
Figure 9 Fuzzification of ALS value 29
Figure 10 Fuzzification of signal value 31
Figure 11 Indoor environment in example 33
Figure 12 The screen of experimental environment 38
Figure 13 Result of primary experiment 43
Figure 14 Result of experiment join FUZZY 44
Figure 15 The experiment of different quantity of reference tags 44
Figure 17 Repeatedly experiment of comparison with LANDMARC 45

List of Tables

Table 1 The table signify data type of tags 25
Table 2 The membership value information of ALS data match 29
Table 3 The membership value information of signal strength data match 31
Table 4 Data types of 9 reference tags in example 33
Table 5 Data types of 1 track tags in example 34
Table 6 The membership value information of ALS data match in example 34
Table 7 The membership value information of signal strength data match in example 35
Table 8 The standard of RFID device in simulation 37
Table 9 Data types of 32 reference tags 40
Table 10 Data types of 20 track tags 41

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