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Title
Enhancing environmental safety: Innovations in radiation monitoring and security with machine learning

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Durlik, Irmina1; Miller, Tymoteusz2; Kostecka, Ewelina3; Sokołowska, Sylwia4; Kostecki, Tomasz5; Zwolak, Rafał6
URI: https://repository.am.szczecin.pl/handle/123456789/2884
2025-12-30
In this article, we delve into the fusion of machine learning (ML) and Internet of Things (IoT) technologies to redefine environmental radiation monitoring and security. By harnessing these advanced technologies, this work presents a novel approach to radiation safety, emphasizing enhanced real-time monitoring, precision in detection, and improved regulatory compliance. Through an in-depth analysis of various case studies and methodologies, it uncovers the potential of ML and IoT in overcoming traditional challenges, such as data accuracy and privacy concerns. The discussion extends to the implications of these technologies on environmental safety, offering a forward-looking perspective on the evolution of radiation monitoring systems. This article not only addresses the technical and ethical challenges but also highlights the transformative impact of ML and IoT integration on public health and environmental protection, paving the way for innovative solutions in the domain of environmental safety and security.
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Title

Enhancing environmental safety: Innovations in radiation monitoring and security with machine learning

Pages

Figures

4

Tables

3

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

10.17402/660

Type

Original scientific article

Journal

84 Scientific Journals of the Maritime University of Szczecin, no. 84 / 2025

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Politechniki Morskiej w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Politechniki Morskiej w Szczecinie

Published

2025-12-30

Recieved

2025-02-17

Accepted

2025-10-08

Funding

No data

Keywords

machine learning, IoT, radiation monitoring, environmental safety, public health, advanced detection systems

URI:

https://repository.am.szczecin.pl/handle/123456789/2884

Language

English

Authors

Durlik, Irmina1; Miller, Tymoteusz2; Kostecka, Ewelina3; Sokołowska, Sylwia4; Kostecki, Tomasz5; Zwolak, Rafał6

Affiliation

1 Maritime University of Szczecin 1-2 Wały Chrobrego St., 70-500 Szczecin, Poland Polish Society of Bioinformatics and Data Science BIODATA 4c Popiełuszki St., 71-214 Szczecin, Poland, i.durlik@pm.szczecin.pl
2 Polish Society of Bioinformatics and Data Science BIODATA 4c Popiełuszki St., 71-214 Szczecin, Poland University of Szczecin, Institute of Marine and Environmental Sciences 13 Wąska St., 71-415 Szczecin, Poland, tymoteusz.miller@usz.edu.pl
3 5 Maritime University of Szczecin 1-2 Wały Chrobrego St., 70-500 Szczecin, Poland Polish Society of Bioinformatics and Data Science BIODATA 4c Popiełuszki St., 71-214 Szczecin, Poland, e.kostecka@pm.szczecin.pl
4 Polish Society of Bioinformatics and Data Science BIODATA 4c Popiełuszki St., 71-214 Szczecin, Poland, sylwia.sokolowska@gmail.com
5 5 Maritime University of Szczecin 1-2 Wały Chrobrego St., 70-500 Szczecin, Poland, 11637@s.pm.szczecin.pl
6 Polish Society of Bioinformatics and Data Science BIODATA 4c Popiełuszki St., 71-214 Szczecin, Poland,

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