  In the Smart Grid environment, the advent of intelligent measuring devices
facilitates monitoring appliance electricity consumption. This data can be used
in applying Demand Response (DR) in residential houses through data analytics,
and developing data mining techniques. In this research, we introduce a smart
system foundation that is applied to user's disaggregated power consumption
data. This system encourages the users to apply DR by changing their behaviour
of using heavier operation modes to lighter modes, and by encouraging users to
shift their usages to off-peak hours. First, we apply Cross Correlation (XCORR)
to detect times of the occurrences when an appliance is being used. We then use
The Dynamic Time Warping (DTW) to recognize the operation mode used.

Signal Processing;Machine Learning