Enhancing Sustainable Indoor Air: Potted Plants and ML Models for VOC Mitigation

Abstract

Addresses a gap left by the short-term, laboratory-based studies that dominate work on indoor potted plants and air quality. A resource-efficient method was developed to assess the VOC absorption of different plant species over extended periods, identifying species that sustain air-quality improvements in real settings. Machine learning was then used to evaluate and predict absorption behaviour, giving a scalable framework that extends to a wider range of species.