A data-driven predictive maintenance framework for smart buildings: Integrating digital twin and machine learning in HVAC systems

Key Points

• The predictive maintenance framework improves HVAC system efficiency, potentially reducing energy costs.
• Key evidence shows a projected 20% increase in HVAC system performance based on real-time data analysis.
• Analysis of data-driven techniques demonstrates effective integration of digital twin technology in maintenance strategies.
• Implications highlight the need for further exploration into scaling this framework for diverse building types.