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March 3, 2026
A data-driven predictive maintenance framework for smart buildings: Integrating digital twin and machine learning in HVAC systems
RW
Ruonan Wang
Northeast Forestry University
Puntos clave
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.
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Ruonan Wang (Thu,) studied this question.
synapsesocial.com/papers/69a75e31c6e9836116a289a4
https://doi.org/https://doi.org/10.1016/j.jobe.2026.115416
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A data-driven predictive maintenance framework for smart buildings: Integrating digital twin and machine learning in HVAC systems | Synapse