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Title: The Automatic Monitoring of Pigs Water Use by Cameras
Authors: Kashiha, Mohammadamin ×
Bahr, Claudia
Amirpour Haredasht, Sara
Ott, Sanne
Moons, Christel
Niewold, Theo
Odberg, Frank
Berckmans, Daniel #
Issue Date: Jan-2013
Publisher: Elsevier
Series Title: Computers and Electronics in Agriculture vol:90 pages:164-169
Abstract: Every year over 59 billion animals are slaughtered for worldwide food production. The increasing demand for animal products has made mass animal breeding more important than ever. Satisfying the needs of the market, farmers will have to use automatic tools to monitor the welfare and health of their animals since manual monitoring is expensive and time consuming. Literature has shown that water use of pigs relates to important variables such as inside temperature, food intake, food conversion, growth rate and health condition. So, water use might be an interesting indicator for automatic monitoring pigs’ health or productivity status. Therefore, we tried to find a cheap and elegant way to monitor continuous water use in a group of pigs in a farm pen. This study comprised four groups of piglets, each group of ten animals in a pen. On average, in the beginning of experiments pigs had a weight of 27 kilograms and in the end they gained weight up to 40 kilograms. Using a water-meter for each pen, water use rate was measured and monitored minutely. The pig house was also equipped with Charge-coupled device (CCD) cameras. Each pen was monitored for 13 days using a camera which was installed above the pen to generate top-view images. There was a water outlet in the corner of each pen. Employing image processing algorithms, drink nipple visits were monitored automatically. Using data of a performed experiment comprising three weeks of data recordings, the relationship between water use and drink nipple visits was investigated. Results showed that by developing a data-based dynamic model of the visits to the drink nipple observed in videos, half-hourly water use could be estimated with an accuracy of 92 per cent.
ISSN: 0168-1699
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Division of Livestock-Nutrition-Quality
Division M3-BIORES: Measure, Model & Manage Bioresponses
× corresponding author
# (joint) last author

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