Digital Twin for real-time monitoring and management
A virtual replica to monitor and manage heritage buildings in real time.
The Digital Twin is a dynamic virtual replica of a cultural heritage building that brings together data, simulation, and visualisation to enhance conservation and operational management. By integrating detailed Building Information Models (BIM) with real-time sensor data, the Digital Twin provides an intelligent digital environment for analysing building performance, detecting issues, and testing interventions before they are implemented.
Key Features
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3D visualisation
Explore buildings through BIM-based interfaces for detailed structural and spatial understanding, and visualize building pathologies.
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Real-time and historical monitoring
Track indoor environmental quality (IEQ) performance over time.
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Automatic anomaly detection
Identify irregular sensor readings and system incidents without manual intervention.
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Performance scoring and benchmarking
Compare current operation against optimal models to highlight inefficiencies.
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Scenario simulations and what-if analysis
Test conservation measures and behavioural changes to evaluate potential outcomes.
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Predictive analysis
Evaluate condensation risks and support preventive maintenance strategies, including temperature and relative humidity predictions.
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Integrated control panel
Navigate, analyse, and report on building performance through a unified interface.
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Full interoperability
Connect seamlessly with monitoring systems using MQTT, APIs, and other data exchange protocols.
Benefits
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Allows a complete understanding of building performance
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Quantifies energy savings before implementation
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Detects risks in advance to support long-term preservation
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Visualises all building metrics in a clear, intuitive 3D interface
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Enables real-time inspection and monitoring from any location
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Built with scalable, modular technologies that integrate with existing systems
How it works
This digital ecosystem enables remote monitoring and management of heritage buildings by integrating energy efficiency, indoor environmental quality (IEQ), and preventive conservation into a single platform. The system combines static BIM data, real-time sensor measurements, and simulation models to provide both insight and foresight, helping operators, conservation specialists, and managers make informed decisions that balance comfort, efficiency, and preservation.
Users can visualise buildings in 3D, track real-time and historical performance, run what-if simulations, and receive automatic alerts on anomalies or inefficiencies. The platform continuously collects data from BIM models, including geometry, materials, lighting, and HVAC systems, as well as dynamic sensor readings of temperature, humidity, CO₂, lighting, and outdoor conditions.
Advanced algorithms process this data in real time to detect irregularities, calculate performance scores, benchmark against optimal operation models, and predict risks such as surface condensation.
Built on a modular and scalable architecture using Kubernetes for container management, Apache Kafka for data streaming, MongoDB and PostgreSQL for structured and unstructured data, Python and EnergyPlus for analysis and simulation, and React with Autodesk Platform Services for responsive 3D visualisation, the system transforms complex building data into actionable insights, empowering heritage managers to preserve historic structures while optimising operational performance.
