RealForAll: real-time system for automatic detection of airborne pollen
Danijela Tešendić, Danijela Boberić Krstićev, Predrag Matavulj, Sanja Brdar, Marko Panić, Vladan Minić, Branko Šikoparija
Abstract
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.