Skip to main content
IBDT Intelligent Buildings Digital Twinning University of Toronto

IBDT · University of Toronto

Understanding Digital Twins

How digital twins work, what they make possible, and why they are changing the way buildings are designed, operated, and renewed.

A digital twin is a virtual counterpart of a physical facility. Below we outline four levels of capability—and how IBDT applies them on campus. For IBDT’s full replicate-reality mandate, see What We Do.

What Is a Digital Twin?

A digital twin is a virtual counterpart of a physical facility. It connects the models, documents, and live data that describe a building, so the virtual and the physical can inform each other. Digital twins operate at four levels of capability:

Descriptive

Presents the current state of assets, systems, and operations—what is happening now.

Predictive

Anticipates what is likely to happen next—demand, degradation, and performance trajectories.

Prescriptive

Evaluates possible courses of action and ranks options against operational constraints.

Generative

Proposes new layouts, sequences, or retrofit strategies, subject to engineering validation.

Why It Matters

  • Retrofits and renewals are costly. A digital twin allows options to be examined virtually before scope and budget are committed.
  • Maintenance and capital planning improve when cost, risk, and asset condition are analyzed together rather than in separate systems.
  • Energy and carbon reporting depend on consistent, well-governed meter and asset data.
  • Owners, operators, and researchers can work from a single trusted source of building data—the foundation of our Data Portal.
Illustration linking a physical building to a virtual model through data layers

Why the University of Toronto

The campus offers a rare combination of scale, diversity, and access—a full-scale environment for developing and validating digital twin methods.

Scale

More than 150 buildings of different ages, types, and systems under a single owner—methods developed here must generalize.

Data Diversity

Sensor and meter data coexist with BIM models, drawings, and work orders—the same mix found in any large building portfolio.

Direct Collaboration

Researchers work alongside the Facilities & Services teams who operate the campus, keeping research grounded in real operations.