Model-Based Clustering of RF-EMF Monitoring Data to Analyze Time Variability(Conference Paper)
- aUniversità Degli Studi di Napoli Federico Ii, Dieti - Dipartimento di Ingegneria Elettrica e Delle Tecnologie Dell'Informazione, Napoli, Italy
- bUniversity of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
- cInstitute BioSense, University of Novi Sad, Novi Sad, Serbia
Abstract
Human exposure to electromagnetic fields (EMFs) has increased over the years because of the significant evolution of cellular network technologies. The growing interest in studying the time behavior of exposure levels requires employing innovative monitoring systems and data analysis techniques. Since 2017, the Republic of Serbia has used the national EMF RATEL network to monitor EMFs continuously over its territory. To enhance the available information on EMF, this paper uses mixture distributions in a model-based clustering approach to analyze the time variability of EMF data and determine if the field strength has any time pattern, focusing on a kindergarten as a case study of a sensitive area. Results show that Log-Normal Mixture Model (LNMM) usually performs better than its Dirichlet-process extension. For workdays, peak and trough values are grouped separately and two additional intermediate clusters are identified; for holidays, only two clusters are identified, possibly for the smaller range of values and flatter behavior over time. © 2024 IEEE.
Indexed keywords
| Engineering controlled terms: | 4G mobile communication systems |
|---|---|
| Engineering uncontrolled terms | 4g LTE5g NRAnalysis timeElectromagneticsField monitoring dataHuman exposuresModel-based clusteringTime variabilityWide-bandWideband monitoring |
| Engineering main heading: | 5G mobile communication systems |
Funding details
| Funding sponsor | Funding number | Acronym |
|---|---|---|
| F/310290/01-04/X56 | ||
| 142-451-3469/2023-01/02 | ||
| 451-03-65/2024-03/200156 |
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1
The paper is partially supported by the Ministero delle Imprese e del Made in Italy through project \"ISPEDIA - Innovazione ed efficienza per l'ISPezione di infrastrutture mediante l'impiego di Droni, Intelligenza Artificiale e smart device\" (grant number F/310290/01-04/X56), by the Provincial Secretariat for Science and Technological Development of the Autonomous Province of Vojvodina, through grant 142-451-3469/2023-01/02, and by the Ministry of Science, Technological Development and Innovations of the Republic of Serbia, through grant 451-03-65/2024-03/200156.
- ISBN: 979-835037053-9
- Source Type: Conference Proceeding
- Original language: English
- DOI: 10.1109/MN60932.2024.10615478
- Document Type: Conference Paper
- Publisher: Institute of Electrical and Electronics Engineers Inc.
Pasquino, N.; Università Degli Studi di Napoli Federico Ii, Dieti - Dipartimento di Ingegneria Elettrica e Delle Tecnologie Dell'Informazione, Napoli, Italy;
Solmonte, N.; Università Degli Studi di Napoli Federico Ii, Dieti - Dipartimento di Ingegneria Elettrica e Delle Tecnologie Dell'Informazione, Napoli, Italy;
© Copyright 2024 Elsevier B.V., All rights reserved.
Cited by 1 document
(2024) IEEE Access