Building Energy Rating

Building Energy Rating (BER) systems aim to quantify a building's energy efficiency, informing owners, policymakers, and urban planners about energy-saving opportunities and carbon emission reduction potential. Current research focuses on improving BER accuracy by addressing data inconsistencies through techniques like self-supervised contrastive learning and by leveraging diverse data sources, including satellite imagery, street-level photos, and building automation system sensor data, often employing machine learning models such as support vector machines and neural networks for analysis and prediction. Accurate and reliable BER assessments are crucial for effective energy policy, building design improvements, and ultimately, mitigating climate change.