Buildings account for 28% of global energy-related CO₂ emissions (37% when including construction), which is more than the entire transportation sector.

While Building management systems have evolved dramatically— many asset managers, building managers, sustainability leaders struggle with siloed data, incompatible systems, and the inability to scale solutions to inform energy performance strategies across diverse building portfolios.

What if there was a way to make these systems truly "understand" buildings by profiling their energy performance with little data by taking into account the characteristics of their envelope as well as their energy consuming devices, while continuously optimising their overall performance?

The Challenge: Why Traditional Building Management Falls Short

Traditional building management systems operate in isolation. A Schneider system can't easily communicate with a Siemens system. Each building requires bespoke intelligence whereby control algorithms must be rewritten from scratch for every new property. This approach is:

• Time-consuming and error-prone

• Lacking portability across buildings

• Limited in scalability

• Difficult to audit for security and trustworthiness

It's like trying to manage a multinational team where each person speaks a different language with no translator available.

Enter Semantic Digital Twins with a Little Extra Context

Semantic digital twins represent a fundamental shift in how we approach building intelligence. Just as Web 1.0 evolved to Web 2.0 through the power of semantics (enabling search engines to understand content rather than just display it), semantic modelling creates a framework where building management systems can truly "understand" their indoor and outdoor environment, including the variability of occupancy across time, with minimal reliance on sensors and controllers.

Example: Semantics digital twins developed through bringing data together on the Optimise Platform

What Makes Semantics So Special?

Semantics provides three key advantages that transform building management:

1. True Scalability Rather than coding for specific components like "Door 110 on the ground floor," semantic models work with classes like "door" in a generic sense. This means algorithms can be applied to any building with minimal readaptation —dramatically accelerating deployment across portfolios.

2. Contextual Intelligence Semantic models create a network of information where relationships between objects are understood. For example, when a hot water tap is turned on, the system understands this will trigger the boiler, affecting energy consumption—even though these components might seem unrelated.

3. Explainable AI With semantics, algorithms become transparent and auditable. You can trace exactly which variables feed into algorithms and understand their impact. This creates trust—crucial for sustainability managers who need to validate energy-saving claims.

Practical Benefits for Building Managers, Asset Managers and Sustainability Leaders

How does this translate to your daily work? Semantic digital twins enable:

• Portfolio-wide deployment: Scale solutions across your entire building portfolio without custom coding for each property

• Deeper insights: Discover unexpected connections between building systems that impact sustainability metrics

• Trustworthy results: Verify exactly how AI recommendations are generated and justify investments to stakeholders

• Future-proofing: As building systems evolve, semantic models adapt without requiring ground-up redevelopment

The Decade of Data Advantage

The most advanced semantic building solutions, like those pioneered at OptimiseAI, have been developed through years of research across multiple domains. These solutions have been tested and refined through collaborations with organizations like Intel, Schneider, Siemens and many others.

Example: Comparing actual building with simulated performance using the Optimise Platform

Each research project has contributed unique insights—from district heating systems to smart water management to community energy sharing. This comprehensive approach means today's semantic models are robust enough to handle the full complexity of the built environment.

Getting Started with Semantic Digital Twins

If you are looking to employ semantic digital twins for your buildings consider the following:

1. Assess your current challenges: Where are your existing building management systems falling short?

2. Consider scalability needs: How many buildings do you manage, and how diverse is your portfolio?

3. Identify interoperability gaps: Which systems in your buildings need to communicate but currently can't?

4. Evaluate your data strategy: How could connected building data transform your sustainability initiatives?

Moving Forward

Semantic digital twins represent not just an incremental improvement but a fundamental shift in building intelligence. By enabling systems to understand context, make connections between seemingly unrelated components, and scale across diverse portfolios, they offer those managing building estates, operational costs and sustainability plans powerful new tools to achieve ambitious decarbonisation and cost reduction goals.

As you evaluate new technologies for your sustainability strategy, consider not just what a solution can do today, but how it can grow and adapt across your entire portfolio tomorrow. The semantic advantage may be the difference between incremental improvements and transformative change.

________________________________________

Ready to explore how semantic digital twins could transform your sustainability initiatives? Connect with our team to learn more about implementation strategies and success stories from organizations similar to yours.

Email us to find out more here

Get started with Predict here