About this document

Personalized Thermal Comfort in Smart Buildings by Akash A is a document available to read on EtoBox.

The document presents a Digital Twin (DT) based deep learning framework that utilizes an Attention-based LSTM model for personalized thermal comfort prediction and energy-efficient HVAC operation in smart buildings. It addresses the limitations of traditional models by capturing individual preferences and temporal dynamics, achieving an accuracy of 83.8% in predicting thermal sensations. The framework also emphasizes explainability through SHAP and LIME, demonstrating energy savings and optimal comfort zone

Author

Akash A

Language

EN