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Why digital twins could help to shape the future of real estate
What is it: Knight Frank’s April 2, 2025 article explores how digital twin technology is emerging as a transformative tool in real estate. A digital twin is a dynamic, virtual replica of a physical building or asset, continuously updated with real-time operational and environmental data. The technology enables simulation-based modeling for performance optimization, energy efficiency, sustainability benchmarking, and strategic investment decision-making. Experts at Knight Frank demonstrate its application in Energy Performance Certificates (EPCs), embodied carbon measurement, asset valuation, and predictive maintenance.
Stakeholder Audience: Facility managers, sustainability leads, asset investors, ESG & finance teams, valuer/advisory professionals.
Inform or Action: This item is both informative and action oriented. It educates BLM stakeholders on digital twin capabilities and encourages them to explore adoption through pilot programs, ESG-aligned valuation frameworks, and integration into capital investment strategies.
Relevance to BLM Principles: Digital twin adoption advances Building Lifecycle Management goals by enhancing data transparency and enabling proactive lifecycle decisions. It supports precise sustainability management and capital deployment—core BLM tenets.
#BLMI #IFMA #Autodesk #DigitalTwin #PropTech #ESG #KnightFrank
Digital Intelligence in Building Lifecycle Management
What is it: A new academic study published in MDPI Sustainability explores a digital twin and genetic algorithm (GA)-based approach for optimizing facade maintenance in commercial buildings. Developed by engineering faculty across Chinese institutions, the research presents a multi-objective framework integrating building lifecycle data with evolutionary algorithms to improve long-term maintenance planning. The method enables cost and performance optimization, balancing trade-offs between safety, aesthetics, and lifecycle value.
The authors argue that digital twin integration—when combined with GA modeling—offers a breakthrough in automating complex decisions in building operations. Using simulated aging models and data from Chinese commercial properties, the study demonstrates measurable gains in maintenance scheduling efficiency and cost-effectiveness.
This research aligns closely with the Building Lifecycle Management (BLM) framework, which advocates for data-driven, lifecycle-integrated decision-making across design, construction, and operations.
Stakeholder Audience: Facility Operations, Corporate-Institutional Owners, Technology Providers-Integrators, Building Owners, AEC, Sustainability-Resiliency, Service Providers-Consultants, Organizational Leadership
Inform or Action: Informational
#BLMI #IFMA #Autodesk #DigitalTwins #GeneticAlgorithms #BuildingMaintenance #LifecycleOptimization #SmartBuildings #Sustainability #MDPI
