A finite state machine-based characterization of building entities for monitoring and control

Cyber physical systems such as buildings contain entities (devices, appliances, etc.) that consume a multitude of resources (power, water, etc.). Efficient operation of these entities is important for reducing operating costs and environmental footprint of buildings. In this paper, we propose an entity characterization framework based on a finite state machine abstraction. Each state in the state machine is characterized in terms of distributions of sustainability or performance metrics of interest. This framework provides a basis for anomaly detection, assessment, prediction and usage pattern discovery. We demonstrate the usefulness of the framework using data from actual building entities. In particular, we apply our methodology to chillers and cooling towers, components of a building HVAC system.