Automated algorithm for classification of water-flow signals to support Ambient Assisted Living applications

Characterization of a home water-flow signal, as an outcome of an analysis of the most appropriate representation in time, frequency and time-frequency domain, has not been adequately studied; mainly due to lack of such specific need. Nevertheless, being able to characterize a water-flow signal in the home-environment can support Ambient Assisted Living systems to determine the activity of a senior citizen, thus contributing to the daily pattern recognition, as well as to identify critical situation. This has triggered our research activities to develop an automated decision-making algorithm for detection of different water-flows that may be found in an ordinary bathroom. The preliminary results will be presented in this paper. The time-frequency representations are employed to analyze and characterize different water-flow signals, as well as to provide input parameters for the algorithm. These approach and algorithm can be used in numerous applications where automated decision-making scenario is required.