Quality-Workload Tradeoff in Pig Activity Monitoring Application

  • Haelyeon KimEmail author
  • Yeonwoo Chung
  • Sungju Lee
  • Yongwha Chung
  • Daihee Park
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 274)


Generally, there is a tradeoff between quality and computational workload required to obtain that quality. In this paper, we focus on practical issues in implementing a pig activity monitoring system. We first propose a method for evaluating the quality-workload tradeoff in the activity monitoring application. Then, we derive the cost-effective solution within the acceptable range of quality for the activity monitoring application. Based on the experiments with the video monitoring data obtained from a pig farm, our method can derive the cost-effective resolution size and frame rate without degrading the accuracy significantly.


Activity Monitoring Quality Accuracy Workload Tradeoff 


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  1. 1.
    Hwang, J., Yoe, H.: Study of the Ubiquitous Hog Farm System using Wireless Sensor Networks for Environmental Monitoring and Facilities Control. Sensors 10, 10752–10777 (2010)CrossRefGoogle Scholar
  2. 2.
    Hwang, J., Shin, C., Yoe, H.: Study on an Agricultural Environment Monitoring Server System using Wireless Sensor Networks. Sensors 10, 11189–11211 (2010)CrossRefGoogle Scholar
  3. 3.
    Berckmans, D.: Automatic On-line Monitoring of Animals by Precision Livestock Farming. In: Keynote in the ISAH Conference “Animal Production in Europe: The Way forward in a Changing World”, vol. 1, pp. 27–30 (2004)Google Scholar
  4. 4.
    Cox, S. (ed.): Precision Livestock Farming. Academic Pub. (2003)Google Scholar
  5. 5.
    Davies, E.: The Application of Machine Vision to Food and Agriculture: a Review. The Imaging Science J. 57, 197–217 (2009)CrossRefGoogle Scholar
  6. 6.
    Frost, A., Schofield, C., Beaulah, S., Mottram, T., Lines, J., Wathes, C.: A Review of Livestock Monitoring and the Need for Integrated Systems. Comput. Electron. Agric. 17, 139–159 (1997)CrossRefGoogle Scholar
  7. 7.
    Ruiz-Garcia, L., Lunadei, L., Barreiro, P., Robla, J.: A Review of Wireless Sensor Technologies and Applications in Agriculture and Food Industry: State-of-the-art and Current Trends. Sensors 9, 4728–4750 (2009)CrossRefGoogle Scholar
  8. 8.
    Wathes, C., Kristensen, H., Aerts, J., Berckmans, D.: Is Precision Livestock Farming an Engineer’s Daydream or Nightmare, an Animal’s Friend or Foe, and a Farmer’s Panacea or Pitfall? Comput. Electron. Agric. 64, 2–10 (2008)CrossRefGoogle Scholar
  9. 9.
    Ekesbo, I.: Farm Animal Behavior: Characteristics for Assessment of Health and Welfare. CAB International (2011)Google Scholar
  10. 10.
    Brehme, U., Stollberg, U., Holz, R., Schleusener, T.: ALT Pedometer — New Sensor-Aided Measurement System for Improvement in Oestrus Detection. Comput. Electron. Agric. 62, 73–80 (2008)CrossRefGoogle Scholar
  11. 11.
    Hu, W., Tan, T., Wang, L., Maybank, S.: A Survey on Visual Surveillance of Object Motion and Behaviors. IEEE Tr. Systems, Man, and Cybernetics – Part C34, 334–352 (2004)Google Scholar
  12. 12.
    Lian, C., Chien, S., Lin, C., Tseng, P., Chen, L.: Power-Aware Multimedia: Concepts and Design Perspectives. IEEE Circuits and Systems Magazine, 26–34 (2007)Google Scholar
  13. 13.
    He, Z., Cheng, W., Chen, X.: Energy Minimization of Portable Video Communication Devices based on Power-Rate-Distortion Optimization. IEEE Tr. Circuits and Systems for Video Technology 18(5), 596–608 (2008)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Haelyeon Kim
    • 1
    Email author
  • Yeonwoo Chung
    • 1
  • Sungju Lee
    • 1
  • Yongwha Chung
    • 1
  • Daihee Park
    • 1
  1. 1.Dept. of Computer and Information ScienceKorea UniversitySejongKorea

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