Detecting Anomalous Energy Consumptions in Smart Buildings – an Overview of Two Unsupervised Techniques

In context of the increasing importance of monitoring our energy consumption due to our energy reserves running short, this paper gives an overview of existing possibilities to detect anomalous energy consumptions in smart cities based on unsupervised machine learning. After defining and presenting different types of anomalies, practical applications and methods for anomaly detection in context of smart cities are discussed.