臺灣博碩士論文加值系統

無線感測網路中偵測與可視連續物體一直是一項重要的議題。由於連續物體像是氣體之類的，當它洩漏時會使人們處於危險當中甚至會導致爆炸之類的重大傷害。然而氣體的特性使得人們難以找到洩漏氣體的準確區域。因此必須解決這個嚴重的問題以免人們不小心進入到危險的區域中導致不可避免的傷害並且也可以幫助救援隊能夠更快的找出洩漏的源頭解決問題。有許多相關的文獻也著重在偵測及可視連續物體的區域或是找出連續物體的邊界，但都比較偏向以靜態的方式來偵測。因此本篇論文採用可以移動的節點，提出邊界區域偵測並經由移動節點精煉邊界區域的演算法。提出的方法分為幾個階段，首先透過不同的邊界區域計算方法像是convex-hull或是Delaunay triangulation，判定感測器是否在事件區內。接著使用節點移動的演算法，透過不斷重複移動來精煉邊界區域。本文也根據邊界區域偵測技術的不同來擬定不同的移動策略。最後本文更提出邊界精煉的機制與節點補位的機制更精確標示出連續物體區域。實驗結果顯示，透過以上方法不僅可以檢測可視連續物體邊界區域，也可以透過提出的移動演算法與機制來精煉更好的邊界區域。

Detecting and visualizing intangible continuous object is a significant issue in wireless sensor networks. Because of the leakage of the continuous object such as gas may involve people in danger and even leads to the explosion. However, the characteristics of the gas event make it difficult to find the accurate dangerous area of the leaking gas. This critical problem must be solved to avoid people entering the hazardous area and help rescue task force finds the leakage source easier. There are lots of related literatures focusing on visualizing the area of the continuous object or detecting the boundary line of the continuous object; however, most of them are static for detecting and visualizing the continuous object. Therefore, this thesis adopts sensor nodes that are mobile and proposes the boundary area detecting and refining algorithms to solve the critical problem by moving the sensor nodes. The proposed methods divide into several stages. First, the boundary area detection is in charge of distinguishing the sensor nodes whether they are inside the continuous object or not. Then, based on different techniques, such as the convex-hull and the Delaunay triangulation, estimate the initial boundary area with different algorithms. Furthermore, the moving algorithm is proposed to refine the boundary area by iterating this procedure until the condition of the end achieves. There are different moving strategies according to the methods of boundary detection in the moving procedure. Subsequently, the sensor nodes replacement mechanism and the boundary refinement mechanism are proposed to help us find a more precise area of the continuous object. Finally, the experiments have showed that these proposed methods not only detect and visualize the boundary area but also refine the boundary area by applying the moving algorithms and mechanisms.

摘要.....i
Abstract.....ii
Acknowledgements.....iv
Content.....v
List of Tables.....vii
List of Figures.....viii
Symbols.....x
Chapter 1 Introduction.....1
1.1 Background.....1
1.2 Motivation.....3
1.3 Objective.....4
1.4 Organization.....4
Chapter 2 Related Works .....5
2.1 Related literatures.....5
2.1.1 Based on Cluster Structure.....5
2.1.2 Based on Planarization Algorithm.....6
2.1.3 Others.....9
2.2 Related Technique.....11
2.2.1 Convex-hull.....11
2.2.2 Delaunay Triangulation.....14
Chapter 3 Proposed Methods.....16
3.1 Assumptions.....16
3.2 The Boundary Area Detection Mechanism.....17
3.2.1 The Detection Mechanism based on the Delaunay Triangulation.....17
3.2.2 The Detection Mechanism based on the convex-hull.....19
3.3 The Moving algorithm.....23
3.3.1 The Moving Algorithm based on the Delaunay Triangulation.....23
3.3.2 The Moving Algorithm based on the convex-hull.....26
3.4 The Sensor Node Replacement Mechanism.....29
3.5 The Boundary Refinement Mechanism.....30
Chapter 4 Experiments.....33
4.1 Environment Assumptions.....33
4.2 Numerical Results.....35
4.2.1 Performances with varying the number of sensor nodes and communication range based on Delaunay triangulation.....36
4.2.2 Performances with varying the number of sensor nodes and proportion of moving distance based on Delaunay triangulation.....40
4.2.3 Performances with varying the number of sensor nodes and communication range based on the convex-hull.....45
4.2.4 Performances with varying the number of sensor nodes and proportion of moving distance based on the convex-hull.....50
4.2.5 Performances with other parameters.....55
Chapter 5 Conclusions.....59
Reference.....60

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