Evaluation of Human Behavior Estimation of Smart Tap using Self-Diagnostics

Solutions to social problems such as an unattended death of the elderly living alone has been demanded. Systems for monitoring the living condition of a person in a remote house using the power consumption data obtained via HEMS or the like have been studied and developed. There are two types of techniques for obtaining power consumption data for life monitoring systems: One method utilizes a smart meter installed in each home by an electric power company. The other method utilizes a smart tap installed by users as needed. In our past research, which was focused on a life monitoring system using a smart tap, we classified home electronics into four categories according to their operations based on the power consumption data obtained with the smart tap, and clarified what types of household electric appliances are suitable for life monitoring. We have aimed at providing a system which allows even individuals without expert knowledge to monitor their lives using smart taps. This time, we developed a self-diagnostic tool that helps to find optimum home appliances for life monitoring. When building a life monitoring system with a smart tap using this self-diagnosis tool, we validated and evaluated whether we can accurately estimate four human behaviors: getting up, going out, getting home, and going to bed. As a result, we confirmed that our proposed method can estimate human behaviors with higher accuracy than smart meters.