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研究生: 李弘翔
Li, Hung-Hsiang
論文名稱: 應用無線感測網路之水污染偵測及追蹤系統
AquaView: An Aquatic-Pollution Detection and Tracking Scheme for Water-Surface Wireless Sensor Networks
指導教授: 林輝堂
Lin, Hui-Tang
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年: 2010
畢業學年度: 98
語文別: 中文
論文頁數: 55
中文關鍵詞: 叢集式網路水面無線感測網路水污染偵測追蹤
外文關鍵詞: Cluster Scheme, Wireless Sensor Network, Water Pollution, Detection, Tracking
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  • 近年來隨著全球工業化的不斷演進與擴張,加上大量船隻頻繁往來各地水域,使得水污染(例如:原油或透明化學原料外洩、有害藻類增生等)的情形日益嚴重。這些污染源若無法有效監控與清除,不但會危害水中生態,甚至影響整個地區的經濟效益。有鑑於此,本碩士論文將提出一套基於佈建在水面之無線感測網路(Water-surface Wireless Sensor Network, 簡稱WWSN)之水污染偵測與追蹤系統,簡稱AquaView。此系統以架構叢集式網路為基礎,讓水面上大量的感測節點不需維護額外的地理資訊(例如:鄰點座標、全域或區域性的網路拓墣等),便能迅速得知自身何處,並於感測範圍內,有效地偵測及追蹤逐漸擴散的污染源遍及之輪廓。經由Qualnet模擬軟體實驗結果證明,AquaView展現優異地監控效能與穩定性。

    Spilled invisible pollutions, such as oil or biochemical materials, damage not only the ocean environment but also the regional economics. To prevent such damages from expanding, a wireless sensor network deployed over the ocean, referred to as Water-surface Wireless Sensor Network (WWSN) in this study, is a suitable candidate for timely monitoring of such wide range and continuous moving objects. In WWSN, this study develops an aquatic-pollution detection and tracking scheme, designated as AquaView, based on an autonomous self-localization cluster mechanism. The proposed scheme enables each normal sensor node to automatically discover its location without maintaining the addition information (i.e., the locations of neighboring nodes, a global or a subset of network topology, and so forth) and to efficiently detect and track the boundary of the current moveable pollution in its sensing field. The numerical results obtained using a Qualnet simulator confirm the effectiveness and robustness of the proposed approach.

    中文摘要i 英文摘要ii 誌謝iii 目錄iv 圖目錄vii 表目錄ix 第一章 緒論1 1.1 引言1 1.1.1 水污染之特性與影響2 1.1.2 當前防治方式與缺失3 1.2 無線感測網路概論5 1.2.1 無線感測網路之架構與特性6 1.2.3 能源議題8 1.3 研究動機與目的9 1.4 論文架構9 第二章 相關研究與文獻探討10 2.1簡介10 2.2 物件追蹤11 2.2.1 陸地與水中進行物件追蹤之差異11 2.2.2 獨立物件追蹤12 2.2.3 連續物件追蹤13 2.3 定位機制與路由方式16 2.3.1 定位系統16 2.3.2 路由協定19 2.3.2.1 Flooding19 2.3.2.2 地理資訊路由演算法19 2.4 叢集式網路架構21 2.5 資料聚集23 第三章 水中連續物件偵測與追蹤系統26 3.1 簡介26 3.2 環境初始化27 3.2.1 系統假設27 3.2.2 情境劇本27 3.3 水中連續物件追蹤28 3.3.1 叢集網路建立階段29 3.3.2自我定位暨水中連續物件偵測階段30 3.3.2.1虛擬3D座標系統30 3.3.2.2 自我定位31 3.3.2.3水中連續物件偵測34 3.3.3 資料回傳階段35 3.3.3.1 建立傳輸階層36 3.3.3.2 地理資訊路由法37 3.3.3.3 TDMA資料聚集38 3.3.3.4 描繪連續物件41 3.3.4 總結41 第四章 效能模擬42 4.1 模擬環境42 4.1.1 模擬場景設定43 4.1.2模擬參數與假設43 4.2 模擬結果與分析44 4.2.1 收集邊界資訊所需耗費的通訊成本45 4.2.2 感測節點密度對於估算邊界資訊準確度的影響48 第五章 結論與未來工作50 參考文獻52

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