In a breakthrough for indoor air quality, an international team of researchers led by Amit Rawal from the Department of Textile and Fibre Engineering, IIT Delhi, has developed a machine learning framework to design smarter Heating, Ventilation, and Air Conditioning (HVAC) filters. The innovation aims to make indoor environments cleaner, healthier, and more energy-efficient.
COVID-19 underscored the urgent need for improved indoor air quality, particularly through better air filtration in HVAC systems. However, filters that effectively capture harmful particles often impede airflow, leading to higher energy consumption. The IIT Delhi-led team trained machine learning models on global datasets to predict both filtration efficiency and airflow resistance. Tested with industrial data from Elofic Industries, the framework demonstrated its capability to guide filter designs for practical 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. By harnessing AI, our goal is to make healthier indoor environments accessible to everyone, from schools and hospitals to workplaces and homes,” said Rawal. |
