Visual Analytics System for Energy Data in Smart Cities and Buildings

New sensors and devices are being incorporated in modern buildings and cities to facilitate the understanding of its dynamics and improve its efficiency. With this in mind, the combination of information technology and sensors capable of capturing and sharing energy data with other devices can help solve power consumption problems. However, large volumes of these data are collected and stored uninterrupted, becoming a challenge to analyze it to confirm trends, identify hidden patterns, and outliers to aid in decision-making. As an alternative to address the issue, this paper presents an interactive visual analytics system to understand energy data coming from a smart building or city. This system provides ways to analyze the data at different levels of time granularities for the identification of energy trends, patterns, and data outliers. Moreover, it combines different algorithms that allow fulfilling predictive analysis. An analysis with domain experts demonstrates the feasibility and advantages of using the system to monitor energy data.