A Smart Energy Audit Framework Integrating BIM, IoT, and Multi-Criteria Decision Analysis for Building Energy Performance Optimization

Energy audits are key to improving energy efficiency and supporting decarbonization in buildings. Traditional audits rely on static data, manual inspections, and simple assumptions, which can limit their accuracy and usefulness. This study introduces an innovative energy audit framework that combines Building Information Modelling (BIM), Internet of Things (IoT) monitoring, and multi-criteria decision analysis (MCDA) to enhance the reliability and effectiveness of building energy assessments. The proposed methodology combines BIM-based extraction of geometric and thermophysical building parameters with real-time operational data from IoT sensors. Key energy performance indicators, including specific energy consumption, potential energy savings, investment cost, payback period, and CO₂ emission reduction, are systematically evaluated. To support rational prioritization of energy efficiency measures, a weighted multi-criteria decision approach is applied, enabling transparent and reproducible ranking of retrofit and operational improvement options. The results show that integrating digital building models and continuous monitoring significantly reduces uncertainty in energy performance evaluation compared to traditional audit methods. Control-oriented measures, such as HVAC optimization and intelligent lighting systems, offer the highest short-term benefits, while envelope retrofitting provides substantial long-term energy savings. The proposed framework offers a scalable, data-driven solution for modern energy audits and supports the transition toward smart, energy-efficient, and sustainable buildings.

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