RealForAll: real-time system for automatic detection of airborne pollen

The aim of this paper is to describe a solution suitable for the automation of standard pollen information service (EN 16868:2019). We are describing the RealForAll integrated information system developed for automatic airborne pollen detection and real-time data delivery to end-users. This solution is based on the measurements from the Rapid-E airborne particle monitor. The system incorporates an AI-enabled subsystem based on a convolutional neural network that continuously retrieves raw data from Rapid-E and performs the classification of airborne pollen. The main advantages of this system reflect in real-time data delivery and independence of aerobiology experts during the pollen season.

Automated summary

This paper describes a solution, the RealForAll integrated information system, suitable for automating the standard pollen information service. The system utilizes measurements from the Rapid-E airborne particle monitor to classify airborne pollen and deliver real-time data to end-users. Its main advantages lie in the real-time data delivery and independence from aerobiology experts.