Detail publikace

Advancing Perimeter Security: Integrating DAS and CNN for Object Classification in Fiber Vicinity

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

Originální název

Advancing Perimeter Security: Integrating DAS and CNN for Object Classification in Fiber Vicinity

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This paper presents an advanced perimeter protection system that integrates phase-sensitive Optical Time-Domain Reflectometry ( Φ -OTDR) with Convolutional Neural Networks (CNNs) for real-time event classification near optical fibers. The proposed approach enhances traditional security methods by providing robust monitoring in challenging environments, such as low visibility and large-scale areas. We evaluated multiple signal preprocessing techniques, including Fast Fourier Transform (FFT), Redundant Discrete Fourier Transform (RDFT), Discrete Wavelet Transform (DWT), and Mel-Frequency Cepstral Coefficients (MFCC), to optimize classification accuracy and computational efficiency. While MFCC achieved the highest accuracy (85.61%), RDFT provided the best balance between performance (85.47%) and real-time feasibility, making it the preferred method for deployment. The system successfully differentiates events such as vehicle movement, fence manipulation, and construction work, while anomaly detection capabilities further enhance security by identifying irregular activities with minimal error. These findings demonstrate the potential of integrating fiber-optic sensing with deep learning to develop scalable, real-time perimeter protection solutions for critical infrastructure, border surveillance, and urban security.

Klíčová slova

Convolutional neural networks;distributed acoustic sensing;event classification;perimeter protection;phase-sensitive optical time-domain reflectometry

Autoři

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

Vydáno

8. 4. 2025

Nakladatel

IEEE

Místo

Online

ISSN

2169-3536

Periodikum

IEEE Access

Ročník

13

Číslo

1

Stát

Spojené státy americké

Strany od

63600

Strany do

63610

Strany počet

11

URL

https://ieeexplore.ieee.org/document/10955273

Plný text v Digitální knihovně

http://hdl.handle.net/11012/251063

BibTex

@article{BUT197717,
  author="Adrián {Tomašov} and Pavel {Záviška} and Petr {Dejdar} and Ondřej {Klíčník} and Francesco {Da Ros} and Tomáš {Horváth} and Petr {Münster}",
  title="Advancing Perimeter Security: Integrating DAS and CNN for Object Classification in Fiber Vicinity",
  journal="IEEE Access",
  year="2025",
  volume="13",
  number="1",
  pages="63600--63610",
  doi="10.1109/ACCESS.2025.3558594",
  issn="2169-3536",
  url="https://ieeexplore.ieee.org/document/10955273"
}