Digital Twin
A virtual replica of a physical building that updates in real-time with sensor and operational data.
Definition
A Digital Twin is a dynamic digital representation of a physical building or infrastructure asset that mirrors its real-world counterpart in real-time. Connected to IoT sensors and building systems, digital twins enable predictive maintenance, energy optimization, and operational insights. AI enhances digital twins by analyzing sensor data streams, predicting equipment failures, optimizing building performance, and simulating scenarios before implementing changes in the physical building.
In Depth
A digital twin is a live virtual model of a physical building that continuously updates with real-time data from sensors, building systems, and operational records. Unlike a BIM model (which represents design intent) or an as-built model (which represents a point-in-time snapshot), a digital twin reflects the building's current state and operational history.
The operational value is in predictive maintenance and performance optimization. By connecting the digital twin to the building automation system, AI monitors equipment performance in context — understanding that a chiller's declining efficiency is related to the fouling of condenser tubes, not just a generic performance degradation. This contextual understanding enables targeted maintenance that extends equipment life and prevents unplanned failures.
For facility owners managing building portfolios, digital twins enable portfolio-level analysis — comparing energy performance across buildings, identifying maintenance patterns that indicate systemic issues (like a roofing failure mode that is appearing across multiple buildings of similar age), and optimizing capital investment decisions based on actual building condition data rather than age-based assumptions.
Examples
Predicting HVAC equipment failures before they occur using sensor data analysis
Optimizing building energy consumption based on occupancy patterns
Simulating the impact of renovation scenarios on building performance
Nomic Use Cases
See how Nomic applies this in production AEC workflows:
Compatible Platforms
Nomic integrates with these platforms so you can use digital twin across your existing project data:
Frequently Asked Questions
A Digital Twin is a dynamic digital representation of a physical building or infrastructure asset that mirrors its real-world counterpart in real-time. Connected to IoT sensors and building systems, digital twins enable predictive maintenance, energy optimization, and operational insights. AI enhances digital twins by analyzing sensor data streams, predicting equipment failures, optimizing building performance, and simulating scenarios before implementing changes in the physical building.
Predicting HVAC equipment failures before they occur using sensor data analysis. Optimizing building energy consumption based on occupancy patterns. Simulating the impact of renovation scenarios on building performance.
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