  An approach is described in this work for detecting discomfort moments during
electrical water heater daily usage. The approach employs chromatic analyzing
sensors signals of electrical water heater systems for producing
distinguishable mapping to characterize and identify selected discomfort
moments. The preliminary results obtained indicate that it is possible to
distinguish such events in a non-intrusive approach. Hot water comfort
detection and classification intelligently through human behavior monitoring
and analyses plays an important role in both, energy saving and energy
management. The focus is on recording the discomfort situations followed by
merging system outcomes with efficiency evaluation will be used to provide
helpful recommendations for selecting appropriate operating strategy.
