New Delhi: An international team led by Professor Amit Rawal of the Faculty of Textile and Fiber Engineering, IIT Delhi, has developed a machine learning framework for designing smart air filters for HVAC (heating, ventilation, air conditioning) systems.
By training AI models with a wide set of global data, researchers have created a system that can predict how well a filter cleans the air, and evaluated how it can easily pass through the air. This framework has been validated with industrial data from Elofic Industries Ltd. to highlight the real-world application potential.
“This powerful industrial and cademia partnership demonstrates how artificial intelligence can accelerate innovation, clean indoor air, reduce energy costs, and open up better preparedness for future health crises,” Professor Rawal said.
“Our goal is to ensure that everyone has access to a healthier indoor environment, from schools and hospitals to work and home,” he added.
This study, machine learning-driven strategies for optimal design of heating, ventilation, and air conditioning (HVAC) filter media (https://doi.org/10.1016/j.seppur.2025.134973), have been published in isolation and purification techniques.
The joint efforts brought together researchers and students from IIT Delhi, Borros University, KTH Royal Institute of Technology, NIT Raipur, Bennett University and ELOFIC Industries Ltd. to highlight the power of the academia industry partnership in tackling global challenges.
