Recent works in ubiquitous computing have addressed analysis of electric power for energy conservation by detailing and studying consumption of electrical appliances. Consumer systems for home energy management can provide significant potential energy saving. But most people have only an approximate idea of how much energy they are using and what impacts they could make by changing day-to-day behavior. Hence it is important to develop systems, based on Non Intrusive Appliance Load Monitoring (NIALM) algorithms, in which individual appliance power consumption information is disaggregated from single-point measurements, that provide a feedback in such a way to make energy more visible and more amenable to understanding and control. We contribute with an approach to develop techniques for monitoring consumption of electric power in households. A new algorithm, which detects the load curve of each appliance in a domestic context based on power consumption, is presented.
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