Energy, Simulation and Capital Decisions From One Model: The Machine Readable Building
The industry now holds a great deal: continuous operational data from sensors, meters and control systems; mature machine readable ways of describing building systems; and a full body of specification and asset information created through design, construction and handover. This session looks at what becomes possible when all of it is held in one connected model that a machine can read. It covers four areas of opportunity: simulation grounded in the real components of a real building; capital planning that can be interrogated and evidenced; requirements that a model can verify itself against, including the ability to test a proposed requirement before it is made; and in use performance reaching the manufacturers who can act on it.
Session Speaker
Spacy Bondarenko is a Chartered Architectural Technologist and Fellow of the Chartered Institute of Architectural Technologists, working where the built environment, regulation and data science meet.
She designs and builds the data structures that allow buildings to be understood by machines: asset hierarchies and ontologies, machine readable regulatory logic, and connected models on which simulation, capital planning and compliance can all draw. She brings building information modelling, digital twins, knowledge graphs and applied machine learning together into working systems, delivered at portfolio scale.
She advises private capital and portfolio leadership on asset data and technology in the built environment, and speaks on the next generation of building data infrastructure.
