Published July 16, 2020
| Version v1
Journal article
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RealForAll: Real-time System for Automatic Detection of Airborne Pollen
Authors/Creators
- 1. University of Novi Sad Faculty of Sciences
- 2. BioSensе Institute - Research Institute for Information Technologies in Biosystems, University of Novi Sad
Description
The aim of this paper is to describe a solution suitable for the automation of standard pollen information service (EN16868:2019). 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.
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accepted manuscript-RealForAll system.pdf
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