Extracting Human Behavior Patterns from Appliance-level Power Consumption Data

In order to provide useful energy saving recommendations, energy management systems need a deep insight in the context of energy consumption. Getting those insights is rather difficult. Either exhaustive user questionnaires or the installation of hundreds of sensors are required in order to acquire this data. Measuring the energy consumption of a household is however required in order to find and realize saving potentials. Thus, we show how to gain insights in the context of energy consumption directly from the energy consumption profile. Our proposed methods are capable of determining the user’s current activity with an accuracy up to 98% as well as the user’s current place in a house with an accuracy up to 97%. Furthermore, our solution is capable of detecting anomalies in the energy consumption behavior. All this is mainly achieved with the energy consumption profile.