AI-driven innovations: transforming air filtration for sustainable and healthy buildings

Abstract

The rapid increase in urbanization has swollen city populations, significantly worsening indoor air pollution. This situation has highlighted the pressing need for sustainable and healthy indoor environments, emphasizing the integration of artificial intelligence (AI). To tackle this issue, various air filtration methods have been employed to enhance air quality within buildings. By effectively removing airborne contaminants, these techniques directly address the decline in indoor air quality. This study thoroughly explores the combined impact of integrating AI into diverse air purification technologies, examining air filtration theories, materials, and standards. Several air filtration technologies are assessed with a focus on key factors such as improved air quality, filtration efficiency, energy and cost-effectiveness, thermal comfort, and acoustic resonance. The study evaluates the benefits, drawbacks, and challenges associated with the different air filtering methods. The aim is to provide a comprehensive guide for future research and development in air filtration technologies, leveraging the power of AI to ensure healthy and sustainable building ventilation systems.