What it is
A digital twin is a digital representation of a real-world entity or system whose relationship to the physical counterpart is maintained for a purpose. For cities, scope can range from a building or bridge to a district or network. A 3D model alone is not an operational twin: asset identifiers, update processes, data provenance, and a decision workflow determine whether it stays useful.
Explore the City Digital Twins directory → to browse city models and documented connected twins, with separate implementation, lifecycle, and access classifications.
For asset- and process-level digital twins used in factories and industrial operations, see Industrial Digital Twins & Simulation at Industrial AI Dispatch.
How the system fits together
Reference model
Geometry, asset registers, and stable identifiers represent the place or infrastructure within a stated scope.
Data connections
Sensors, work orders, designs, and geographic layers are joined with timestamps and provenance rather than treated as interchangeable live truth.
Analysis and simulation
Rules or models describe current conditions or test bounded scenarios; assumptions and uncertainty remain visible.
Decision workflow
Planners, operators, and asset owners define which decisions the twin supports and how records are corrected.
- 01
Reference model
- 02
Data connections
- 03
Analysis and simulation
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Decision workflow
Where cities use it
- Building and district operations
- Infrastructure asset management
- Planning and public consultation
- Scenario testing for mobility, heat, flooding, or energy
Data generated
- 3D geometry and imagery
- Asset identifiers and condition records
- Sensor and work-order observations
- Scenario outputs and assumptions
Analytics and AI applications
- Spatial analytics
- Change detection
- Scenario simulation
- Asset risk and maintenance prioritization
Example in practice
Bentley documents the City of Pau’s use of a city digital twin for planning and public consultation. That vendor case study shows a documented use; other cities should check the model’s update cadence, coverage, accessibility, and measured effect on planning decisions. In Japan, Sendai provides a publicly accessible 3D digital twin that allows users to explore the city and its spatial data through an interactive web viewer.
Design considerations
Choose sensor placement and refresh rates from an operational need. Keep device identity, calibration, network health, and location visible to the team using the data.
Limits and risks
- A twin can look precise while depending on stale or incomplete asset data.
- Cross-agency models need clear data ownership, access, and update responsibilities.
- Simulations are conditional estimates; they do not prove a future outcome.