Abstract
The Plants4AQI project introduces an AI-powered aeroponic plant recommender to combat urban airpollution and unsustainable farming. Integrating air quality data, climate variables, and phytoremediation studies through a Retrieval-Augmented Generation (RAG) model, it identifies efficient air-purifying plants. Aeroponics enables resource-light growth, converting urban spaces into natural filters. A prototype demonstrates practical recommendations while addressing sustainability and ethical concerns, positioning Plants4AQI as a scalable tool for urban environmental management.
Keywords: Aeroponics, Real-time Data, Artificial Intelligence, Air Quality Index