Proceedings of the Korean Institute of Information and Commucation Sciences Conference (한국정보통신학회:학술대회논문집)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Farm Damage Prevention System Using Thermal imaging Camera and Deep Learning

열화상 카메라와 딥러닝을 이용한 농가피해방지 시스템

  • Shin, Seung-min (School of Computer Science and Engineering, Kyungpook National University) ;
  • Lee, Sang-hoon (School of Computer Science and Engineering, Kyungpook National University) ;
  • Choi, Hyo-sun (School of Computer Science and Engineering, Kyungpook National University) ;
  • Kim, Seung-hoo (School of Computer Science and Engineering, Kyungpook National University) ;
  • Lee, Cherl-hee (JC RADAR Inc)
  • Published : 2019.05.23
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Abstract

The damage to farms due to wild animals such as wild boars and elks increases every year, but, in the current system, the catchers from government hunt animals by using guns at night as making an effort to detect wild animals personally by using flashlights. This is very time-inefficient and immediate follow-up action on being damaged is not possible. In this paper, we introduce a system which can detect and recognize the wild animals or the people with high accuracy using thermal imaging camera and infrared camera in company with deep learning technology, so that could kick out or catch the wild animals more quickly than current system.

매년 멧돼지, 고라니 등의 야생동물로 인한 농가의 피해가 증가하지만 현 시스템은 정부 측 포수들이 직접 야간에 총과 손전등을 이용해 동물들을 찾아다니며 포획하는 상황이다. 이는 시간적으로 매우 비효율적이며 피해 받는 즉시 즉각적인 조치가 불가능하다. 이에 본 논문에서는 야간에도 동물이나 사람을 인식 할 수 있는 열화상 카메라와 딥러닝을 사용한 적외선카메라를 이용해 야생동물을 탐지하고 쫓아내거나 빠르게 포획 할 수 있는 시스템에 대해서 소개하고자 한다.

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