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A. Mahdavi, M. Taheri:
"An ontology for building monitoring";
Journal of Building Performance Simulation, Special Issue: The fundamentals of occupant behaviour research (2017), 10; 499 - 508.

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 modelpredictive
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.

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 modelpredictive
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.

building monitoring, ontology, building performance, simulation

http://dx.doi.org/10.1080/19401493.2016.1243730

http://www.tandfonline.com/doi/abs/10.1080/19401493.2016.1243730