NEW DELHI: An international team led by Prof. Amit Rawal from the Department of Textile and Fibre Engineering at IIT Delhi has developed a machine learning framework to design smart air filters for HVAC (heating, ventilation and air conditioning) systems.
By training AI models on a wide set of global data, the researchers created a system that can predict how well a filter cleans the air while also assessing how easily air passes through it. The framework was validated with industrial data from Elofic Industries Ltd., highlighting its potential for real-world applications.
“This strong industry–academia partnership demonstrates how artificial intelligence can accelerate innovation, paving the way for cleaner indoor air, lower energy costs, and better preparedness against future health crises,” Prof. Rawal said.
“Our goal is to make healthier indoor environments accessible to everyone—from schools and hospitals to workplaces and homes,” he added.
The 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), has been published in Separation and Purification Technology.
The collaborative effort brought together researchers and students from IIT Delhi, University of Borås, KTH Royal Institute of Technology, NIT Raipur, Bennett University, and Elofic Industries Ltd., underscoring the power of academia–industry partnerships in tackling global challenges.