A team of researchers led by the Indian Institute of Technology Delhi has developed an artificial intelligence tool that can predict the performance of HVAC filters and help design more efficient ones. The development is aimed at improving indoor air quality, which has become increasingly important since the COVID-19 pandemic forced people to spend more time indoors.
The team, which also included researchers from Sweden, explained that filters capable of trapping harmful particles often block airflow, reducing system efficiency and increasing energy use.
Amit Rawal, professor at the department of textile and fibre engineering in IIT Delhi, said, “By training machine learning models on diverse data points collected from studies worldwide, we were able to predict both how well a filter cleans the air and how easily air can pass through it.”
The model was developed by combining experimental data from previously published studies with AI algorithms. It was then tested using industrial data from Elofic Industries Ltd, a Faridabad based manufacturer of filters for automotive and industrial purposes, including HVAC systems. The results confirmed its potential for guiding real world filter design.
Rawal noted, “This strong industry academia partnership demonstrates how AI can accelerate innovation, paving the way for cleaner indoor air, lower energy costs, and better preparedness against future health crises.” He added that the goal is to make “healthier indoor environments accessible to everyone, from schools and hospitals to workplaces and homes.”
The study was published in the journal Separation and Purification Technology. While highlighting the benefits, Rawal also pointed out the challenges of AI, such as lack of interpretability, the need for large training datasets, and high computational demands.
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