Our study examines how real-time pollen monitoring can be enhanced by retraining artificial intelligence models with locally collected data. Using the advanced Swisens Poleno Jupiter device in Wrocław, Poland, we recorded hourly pollen concentration changes and their relationship with meteorological conditions. Locally adapted models provide more accurate, timely information, reveal taxon-specific diurnal pollen variability, and improve allergy risk assessment.