Towards appliance usage prediction for home energy management

In this paper, we address the problem of predicting the usage of home appliances where a key challenge is to model the everyday routine of homeowners and the inter-dependency between the use of different appliances. To this end, we propose an agent based prediction algorithm that captures the everyday habits by exploiting their periodic features. We demonstrate that our approach outperforms existing methods by up to 40% in experiments based on real-world data from a prominent database of home energy usage.