Buildings account for roughly 30% of global energy use, making them a major contributor to emissions and a key target for efficiency improvements. The Conversation article argues that digital twins—dynamic virtual models linked to real-world buildings—could play a critical role in reducing this energy demand by enabling more precise, data-driven management of building systems.
Unlike traditional building models, digital twins continuously update using data from sensors embedded in heating, cooling, lighting, and occupancy systems. This allows operators to monitor performance in real time, detect inefficiencies, and adjust operations accordingly. Instead of relying on fixed schedules or assumptions, building systems can respond dynamically to actual usage patterns, reducing unnecessary energy consumption.
One of the most valuable capabilities is prediction. Digital twins can simulate different scenarios, such as changes in weather, occupancy, or equipment performance, helping managers anticipate problems and optimize energy use before inefficiencies occur. This predictive approach extends to maintenance as well, allowing early detection of faults that might otherwise lead to wasted energy or system failure.
The technology is particularly important for existing buildings, which make up most of the global building stock and often lack modern energy-efficient design. By layering digital intelligence onto these structures, digital twins offer a way to improve performance without requiring costly reconstruction. This makes them a practical tool for large-scale energy reduction efforts.
However, the article also notes challenges. Digital twins depend on high-quality data, integration across fragmented systems, and investment in digital infrastructure. Concerns around cost, interoperability, and data privacy continue to limit widespread adoption.
Even with these barriers, the potential impact is substantial. By turning buildings into responsive, data-driven systems, digital twins could significantly reduce global energy use and help meet climate goals.