An ontology for building monitoring

Abstract

Building data monitoring can provide performance feedback for operational optimization of existing facilities and improve future designs. It can support, amongst other things, energy and performance contracting, smart load balancing, and model-predictive building systems control. However, a closer look at the current practice suggests that the commonly deployed technical infrastructures are not mature enough and their hardware resilience and software interoperability are in need of improvement. To address these issues at a fundamental level, we introduce an ontology for the representation and incorporation of multiple layers of monitored building data in pertinent computational applications. The proposed ontology is grounded on the identification of six basic data categories, namely inhabitants, indoor environmental conditions, external environmental conditions, control systems and devices, equipment, and energy flows. The paper illustrates in detail how these data categories provide an effective classification framework to accommodate the multiplicity of empirical information obtainable from building monitoring systems.