微機電系統是由微感測器、微執行器、信號處理和控制電路、通訊介面和電源等部件組成的一體化的微型器件系統。其目標是把資訊的獲取、處理和執行集成在一起，組成具有多功能的微型系統。

無線感測網路對於寬廣範圍的應用領域開啟了一個新的展望，其中一個在無線感測網路上最主要的應用即為對連續移動物件做偵測和追蹤，像是森林火災、生化原料等，此研究發展一個連續物件偵測和追蹤演算法（Continuous Object Detection and Tracking Algorithm)來處理此議題，命名為CODA，以混合動態／靜態叢集技術為基礎。每一個感測節點經由使用CODA後，不僅可以偵測和追蹤物件移動的邊界且能幫助收集和散播邊緣資訊。經由Qualnet模擬的實驗結果證明此研究所提出的演算法是強健且有效率的。

With the advancement of Micro-Electro-Mechanical Systems
（MEMS） technologies, wireless sensor networks have been
opened new vistas for a wide range of application domains.

One of primary applications in wireless sensor network is
detecting and tracking continuously moving objects, such as wild fire, bio-chemical material, and so forth.

This study addresses this issue by developing a Continuous
Object Detection and Tracking Algorithm, designated as CODA, based on a hybrid dynamic/statistic cluster technique.

Through the use of CODA mechanism, each sensor node not only can detect and track the movement boundaries of objects but also facilitate the fusion and dissemination of boundary information. A series simulation results performed using a Qualnet simulator confirm the effectiveness and efficiency of the proposed algorithm.

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