Kiss, L. Márton and Pintér, Judit Mária and Kósa, Balázs and Markó, Balázs and Veres, Laura (2024) Calibration of particle sensor with neural network algorithm. POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES, August 2024. pp. 1-8. ISSN 1788-1994
![]() |
Text
606-article-10.1556-606.2024.00951.pdf Download (1MB) |
Abstract
Based on air quality index data for the period 2018–2022, Hungary ranks as the 80th most polluted country in the world. Given the air pollution data measured in Hungary and the health impact of air pollution, it is of utmost importance to measure air quality in Hungary focusing on PM10 and PM2.5 pollutants. One possible solution for high-density measurement is to utilize low-cost sensors at the population level. The calibration procedure has to be carried out in a way that does not incur extra costs and maintenance at the physical level. A potential solution is the development of an algorithm to perform the calibration with remote access. This publication presents a fragment of this development, where we attempted to implement the procedure using a neural network and performed a comparative analysis with official data.
Tudományterület / tudományág
engineering and technology
engineering and technology > material sciences and technologies
Faculty
Not relevant
Institution
Soproni Egyetem
Item Type: | Article |
---|---|
SWORD Depositor: | Teszt Sword |
Depositing User: | Csaba Horváth |
Identification Number: | MTMT:35192956 |
Date Deposited: | 30 Sep 2024 07:56 |
Last Modified: | 30 Sep 2024 07:56 |
URI: | http://publicatio.uni-sopron.hu/id/eprint/3279 |
Actions (login required)
![]() |
View Item |