根據相關研究指出住商建築物是未來推動能源效率最有潛力的目標，因此「建築能源管理」逐漸受到重視。建築物能源管理系統的發展使得建築物之能源管理更加容易與便利，並且可以協助能源監測、診斷及解決故障發生之可能原因。然而既有建築受限建築物結構影響，導入能源管理系統需花費相當多的成本與時間。近年來發展之無線感測網路（Wireless Sensor Networks, WSN）是以感測為主要功能所發展出來的網路架構模式，其核心技術在於如何量化且正確收集資訊，可以即時感測無線遠端監測。透過WSN快速安裝、彈性移動及易於管理之特性，可作為大樓能源管理的新應用。因此本研究將探討如何運用WSN來解決既有建築物在能源管理上的困難與其效益。
本研究結合WSN技術與節能資訊系統，提出整合WSN之節能模式架構。以WSN取代傳統感測方式，改善以往在建築物能源監控上的缺失與不足。透過Web Services服務元件方式進行web-based的節能系統雛型的開發，包含三個主要的子功能服務元件，依序為監控感測資料、環境感測資料分析及檢測設備監控。藉由操作此系統可以提升能源控管效率，並且有利於管理者控制、監控與分析資訊，進而達到節能之目的。
論文中以實際案例探討的方式，測試並證實模式的可行性與節能效益。經實證研究後，本研究所提出之模式確實可大幅提升能源監控的即時性，並適時反應環境狀況及監控異常，提升環境舒適品質及減少人為的疏失；同時也驗證整合WSN之節能模式具有明顯節能效益。

Research reports show that residential and commercial buildings hold the greatest potential to improve energy efficiencies. Building energy management has therefore become an important topic recently. Implementation of BEMS (Building and Energy Management System) enables the management of building energy easier and more convenient for the administrators. A modern BEMS is also capable to diagnose the cause of breakdowns, on the energy system, and to resolve it. A traditional BEMS would need to change the architecture of a building and is costly and time-consuming to be implemented in the existing structures. Now that Wireless Sensor Networks (WSN) is becoming a developed technology, it provides engineers to collect data and monitor the key parameters in a building through a flexible way to install. Hence, the application of WSN provides engineers a way to solve the difficulty of implementing BEMS in existed buildings.
The main purpose of this research aims to integrate WSN with BEMS, and subsequently proposes a web-based BEMS model, attempting to improve the shortcomings of existing energy monitoring system. Web Services are provided in the proposed web-based BEMS model, which can observe sensory information, analyze environmental data, and monitor equipment in the Internet. With the availability of this system, energy management efficiency can be enhanced and a case study is used to illustrate its feasibility.
Based on the case study, the proposed model can boost the effectiveness in energy consumption, and to increase the flexibility in monitoring and responding to the data. Further application of the proposed model can be experimented in a wider circumstance.

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