全球能源供需問題日趨嚴重，節能減碳為世界各國發展趨勢。對於住商電力用戶而言，智慧地減少電力消耗與費用支出，其關鍵在於是否可以提供足夠詳細與即時的家電狀態與耗能資訊給消費者。應用非侵入式家電耗能監測技術目前最受到矚目，不過該技術目前的家電辨識準確率跟所使用的家電運作特徵和樣式辨認技術有關，而一般所使用的特徵大都是電壓與電流。本研究應用家庭迴路之電力線通訊（PLC）品質等參數，進行「非侵入式之PLC-based家電偵測技術」之家電設備耗能辨識分析研究，期望利用家電種類與運轉狀態對於電力線通訊（PLC）的影響性作為辨識特徵，除了提高整體系統耗能辨識率以外，更能定位設備或家電，將可讓數位家庭更貼近使用者。

Carbon dioxide emission reduction goals have generated significant interest in greatly increasing the deployment of energy efficiency measures. Prior studies indicate that a better home energy management would reduce 10%~15% energy usages. A key technology is the non-intrusive load monitoring (NILM). A NILM system, in which the appliance usage information is obtained at the main breaker level and the energy management (i.e., control) is realized manually, can present a viable alternative to the home automation network. Usually, the NILM measures the voltage, current, real power, reactive power, or harmonic. In this proposal, we measure an average bit error rate or the average value of the signal to noise ratio by the Power Line Carrier (PLC) technique as new characteristics for NILM, when an appliance works.