Journal of Sensor Science and Technology (센서학회지)

The Korean Sensors Society (한국센서학회)
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Development of Long-perimeter Intrusion Detection System Aided by deep Learning-based Distributed Fiber-optic Acoustic·vibration Sensing Technology

딥러닝 기반 광섬유 분포 음향·진동 계측기술을 활용한 장거리 외곽 침입감지 시스템 개발

  • Kim, Huioon (Optical Precision Measurement Research Center, Korea Photonics Technology Institute) ;
  • Lee, Joo-young (Optical Precision Measurement Research Center, Korea Photonics Technology Institute) ;
  • Jung, Hyoyoung (Optical Precision Measurement Research Center, Korea Photonics Technology Institute) ;
  • Kim, Young Ho (Optical Precision Measurement Research Center, Korea Photonics Technology Institute) ;
  • Kwon, Jun Hyuk (ENITT Co., Ltd.) ;
  • Ki, Song Do (ENITT Co., Ltd.) ;
  • Kim, Myoung Jin (Optical Precision Measurement Research Center, Korea Photonics Technology Institute)
  • 김희운 (한국광기술원 광정밀계측연구센터) ;
  • 이주영 (한국광기술원 광정밀계측연구센터) ;
  • 정효영 (한국광기술원 광정밀계측연구센터) ;
  • 김영호 (한국광기술원 광정밀계측연구센터) ;
  • 권준혁 ((주)에니트) ;
  • 기송도 ((주)에니트) ;
  • 김명진 (한국광기술원 광정밀계측연구센터)
  • Received : 2021.10.26
  • Published : 2022.01.31
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Abstract

Distributed fiber-optic acoustic·vibration sensing technology is becoming increasingly popular in many industrial and academic areas such as in securing large edifices, exploring underground seismic activity, monitoring oil well/reservoir, etc. Long-range perimeter intrusion detection exemplifies an application that not only detects intrusion, but also pinpoints where it happens and recognizes kinds of threats made along the perimeter where a single fiber cable was installed. In this study, we developed a distributed fiber-optic sensing device that measures a distributed acoustic·vibration signature (pattern) for intrusion detection. In addition, we demontrate the proposed deep learning algorithm and how it classifies various intrusion events. We evaluated the sensing device and deep learning algorithm in a practical testbed setup. The evaluation results confirm that the developed system is a promising intrusion detection system for long-distance and seamless recognition requirements.

Keywords

Acknowledgement

본 연구는 행정안전부와 한국산업기술평가관리원의 사회 복합재난 대응기술 개발사업(No. 20015728) 및 중소벤처 기업부와 한국산업기술진흥원의 지역특화 산업육성+(R&D) 사업(No. S2910209)의 지원을 받아 수행된 연구임.

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