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

Authors :
Tešendić, Danijela
Boberić Krstićev, Danijela
Matavulj, Predrag
Brdar, Sanja
Panić, Marko
Minić, Vladan
Šikoparija, Branko
Source :
Enterprise Information Systems; May2022, Vol. 16 Issue 5, p1-17, 17p
Publication Year :
2022

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17517575
Volume :
16
Issue :
5
Database :
Complementary Index
Journal :
Enterprise Information Systems
Publication Type :
Academic Journal
Accession number :
156729663
Full Text :
https://doi.org/10.1080/17517575.2020.1793391