통합 이미지 처리기법 기반의 PLF를 위한 Swine 관리 시스템

A Swine Management System for PLC baed on Integrated Image Processing Technique

  • 투고 : 2014.03.04
  • 심사 : 2014.03.31
  • 발행 : 2014.03.31

초록

세계 인구의 증가로 인하여 식량에 대한 요구 또한 이에 비례하여 증가하고 있는 가운데 지속적으로 안정적인 가축 공급을 위해서는 농장에 대한 효율적인 관리가 중요하다. 최근 여러 가지 기술적 진보와 혁신에 목축업이나 농업 분야의 생산성이 향상되고 있으며, 각종 스마트 센서와 여러 가지 자동화 디바이스를 이용하여 가축의 생육 상태를 지속적으로 모니터링하고 생산을 관리하는 PLF(Precision Livestock Farming)의 활용이 확산되고 있다. 본 논문은 이미지 프로세싱 기법을 이용하여 가축의 체중을 모니터링하는 swine 관리 시스템에 관한 것으로서 Pig Module, Breeding Module, Health and Medication Module, Weighr Module, Data Analysis Module 및 Report Module을 구현하여 카메라를 통해 획득한 이미지를 이용하여 체중을 자동으로 계산하고 먹이량을 조절하며 건강상태도 모니터링 할 수 있도록 하였다.

The demand for food rises proportionally as population grows. To be able to achieve sustainable supply of livestock products, efficient farm management is a necessity. With the advancement in technology it also brought innovations that could be harness in order to achieve better productivity in animal production and agriculture. Precision Livestock Farming (PLF) is a budding concept of making use of smart sensors or available devices to automatically and continuously monitor and manage livestock production. With this concept, this paper introduces a swine management system that integrates image processing technique for weight monitoring. This system captures pig images using camera, evaluate and estimate the weight base on the captured image. It is comprised of Pig Module, Breeding Module, Health and Medication Module, Weighr Module, Data Analysis Module and Report Module to help swine farm administrators better understand the performance and situation of the swine farm. This paper aims to improve the management in both small and big livestock raisers.

키워드

참고문헌

  1. D. Berckmans, "Precision Livestock Farming - Interview Professor Berckman http//www.fancom.com/. 2011.
  2. United Nations website Online. Retrieved http//www.un.org/apps/news/story.asp?NewsID=45165#.Uw6TqOenFEU.
  3. Food and Agriculture Organization Magazine. "World Livestock 2011 Livestock in Food Security," Food and Agriculture Organization of the United Nations. pp. 3, 2011.
  4. J. Pomar, C. Pomar, "A knowledge-based decision support system to improve sow farm productivity". Journal of Expert Systems with Applications. pp. 33-40. 2005.
  5. C. Wathes, "Precision Livestock farming for Animal Health, Welfare and Production", ISAH-2007 Tartu. pp. 397-398. 2007.
  6. D, Berkmans. "Automatic On-Line Monitoring of Animals by Precision Farming", Saint-Malo: International Society for Animal Hygiene. pp. 27. 2004.
  7. C.M. Wathes, H.H. Kristensen, J. M. Aerts, D. Berckmans. "Is precision livestock farming an engineer's daydream or nightmare, an animal's friend or foe, and a farmer's panacea or pitfall?", Journal of Computers and Electronics in Agriculture. pp. 2-10, 2008.
  8. L.E. Zarragoza, "Evaluation of the Accuracy of Simple Body Measurements for Live Weight Prediction in Growing-Finishing Pigs", University of Illinois at Urbana-Champaign. pp. 5-7.2009.
  9. M.B.R. Mollah, M.A. Hasan, M.A. Salam, M.A. Ali, "Digital image analysis to estimate the live weight of broiler", Journal of Computer and Electronics in Agriculture. pp. 48-52. 2010.
  10. M. Kashiha, C. Bahr, S. Ott, C.P.H Moons, T.A.Niewwold, F.O. Odberg, D. Berckmans, "Automatic identification of marked pigs in a pen using image pattern recognition", Journal of Computer and Electronics in Agriculture, pp. 111-120. 2013.
  11. M. Kashiha, C. Bahr, S.A. Haredasht, S. Ott, C.P.H Moons, T.A.Niewwold, F.O. Odberg, D. Berckmans, "The automatic monitoring of pigs water use by cameras", Journal of Computer and Electronics in Agriculture, pp. 164-169, 2013.
  12. Pigcom website Online. Retrieved from http//www.pigcom.co.uk/, 2013.
  13. Sigapig website Online. Retrieved from http//www.softscout.com/software/Agriculture-and-Farming/Livestock-and-Herd-Management/SigaPig.html, 2013.
  14. Herdsman website Online. Retrieved http//www.herdsman.com/, 2013