感測網路近年來被廣泛的應用在居家與社區監控、醫療看護、生產製造監控、工程監控、生態環境監控與軍事用途等，這些應用常常需要長期、連續的監測環境數據的最大或最小值，例如：監測製程廠房或機器的最大溫度。在本篇文章中，我們提出一個感知器網路異常溫度監控省電傳輸演算法，所設計的方法可利用樹狀傳輸結構過濾掉非必要的資料封包，且可依據過去的歷史資料進行各個感測端的回報速率調節，此方法也利用分散回報的方式來減輕極值節點傳輸到中央控制節點傳輸路徑上的所有父節點的流量負擔。本篇論文所提出的演算法與傳統方法比較結果顯示，所提之方法可在錯誤率1%的損失之內，降低20%左右的資料傳送量。

Monitoring abnormal values is important to many applications in wireless sensor networks. A tree-based previous work, called Hierarchy Adaptive Threshold (HAT), was proposed to monitor extreme values (e.g., maximum or minimum values) efficiently by filtering out the unnecessary data updates. In this paper, an energy-efficient algorithm for monitoring extreme values in sensor networks is presented to reduce energy consumption of the HAT. The proposed method utilizes historical information of extreme values and their corresponding node ID to adjust the reporting rate of sensors properly and reduce the traffic burden of extreme nodes by balancing the network transmission among extreme nodes and their parents. The proposed algorithm was evaluated by NS-2 network simulator and real-world data traces. The results indicate that nearly 20% of the overall network packets are reduced with 1% data error as compared to HAT.