Publication detail

Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems

TOMAŠOV, A. ZÁVIŠKA, P. DEJDAR, P. KLÍČNÍK, O. HORVÁTH, T. MÜNSTER, P.

Original Title

Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems

Type

journal article in Web of Science

Language

English

Original Abstract

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).

Keywords

Distributed Acoustic Sensing (DAS);Fiber optic sensor;Perimeter security;event classification;phase-OTDR

Authors

TOMAŠOV, A.; ZÁVIŠKA, P.; DEJDAR, P.; KLÍČNÍK, O.; HORVÁTH, T.; MÜNSTER, P.

Released

14. 5. 2025

Publisher

Nature Portfolio

Location

BERLIN

ISBN

2052-4463

Periodical

Scientific data

Year of study

12

Number

1

State

United Kingdom of Great Britain and Northern Ireland

Pages from

1

Pages to

8

Pages count

8

URL

Full text in the Digital Library

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"
}