Detail publikace
Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems
TOMAŠOV, A. ZÁVIŠKA, P. DEJDAR, P. KLÍČNÍK, O. HORVÁTH, T. MÜNSTER, P.
Originální název
Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
Distributed Acoustic Sensing (DAS) technology leverages optical fibers to detect acoustic signals over long distances, offering high-resolution data critical for applications such as seismic monitoring, structural health monitoring, and security. A significant challenge in DAS systems is the accurate classification of detected events, which is crucial for their reliability. Traditional signal processing methods often struggle with the high-dimensional, noisy data produced by DAS systems, making advanced machine learning techniques essential for improved event classification. However, the lack of large, high-quality datasets has hindered progress. In this study, we present a comprehensive labeled dataset of DAS measurements collected around a university campus, featuring events such as walking, running, and vehicular movement, as well as potential security threats. This dataset provides a valuable resource for developing and validating machine learning models, enabling more accurate and automated event classification. The quality of the dataset is demonstrated through the successful training of a Convolutional Neural Network (CNN).
Klíčová slova
Distributed Acoustic Sensing (DAS);Fiber optic sensor;Perimeter security;event classification;phase-OTDR
Autoři
TOMAŠOV, A.; ZÁVIŠKA, P.; DEJDAR, P.; KLÍČNÍK, O.; HORVÁTH, T.; MÜNSTER, P.
Vydáno
14. 5. 2025
Nakladatel
Nature Portfolio
Místo
BERLIN
ISSN
2052-4463
Periodikum
Scientific data
Ročník
12
Číslo
1
Stát
Spojené království Velké Británie a Severního Irska
Strany od
1
Strany do
8
Strany počet
8
URL
Plný text v Digitální knihovně
BibTex
@article{BUT197921,
author="Adrián {Tomašov} and Pavel {Záviška} and Petr {Dejdar} and Ondřej {Klíčník} and Tomáš {Horváth} and Petr {Münster}",
title="Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems",
journal="Scientific data",
year="2025",
volume="12",
number="1",
pages="8",
doi="10.1038/s41597-025-05088-4",
issn="2052-4463",
url="https://www.nature.com/articles/s41597-025-05088-4"
}