AI-assisted thermal vision for smart cooling of clean rooms

Cleanrooms are highly energy-intensive environments, consuming up to 100 times more energy than typical commercial spaces due to strict requirements for temperature, humidity, and particle control. Conventional HVAC systems often overcompensate, leading to substantial energy waste. This project integrates thermal imaging with deep learning to monitor, classify, and localize heat sources within cleanrooms in real time, providing the foundation for intelligent, adaptive cooling control. We enable data-driven optimization of cooling demand, paving the way for more sustainable, autonomous thermal management systems.