Visualization-assisted Insights into Home Energy Usage

Abstract

Motivated by both cost savings and environmental concerns, managing energy in the home has become increasingly important. Though both user-driven and automated solutions have shown promise, a deeper understanding of the characteristics of energy usage behavior is necessary to inform the design of such systems. In this work, we present the results of a study that explores the insights and characteristics participants are able to derive using two well-known visualization techniques for time series data. We find that participants are able to extract a variety of relevant features and explain general and anomalous patterns of behavior. We also find that the preferred visualization is both user- and task-dependent. These findings may be used as the basis for new systems for home energy management.