Automatic individual pig detection and tracking in pig farms

Over one billion pigs are farmed globally each year and can experience a range of health and welfare problems such as respiratory and enteric diseases and tail biting outbreaks. It is a time consuming and labour-intensive task for farmers and vets to monitor their animals day-to-day. Additionally, animals often change their behaviours in the presence of humans, meaning that we don’t always get a clear picture of the true activity levels in a pen. Being able to remotely monitor the pigs behaviour means that we can quantify normal movement patterns and therefore know when a pig is behaving in an unusual way. Deviations from baseline movement, such as less time spent eating and drinking, can signify potential sickness and can aid farmers in knowing where they should focus their efforts.
The first step in achieving a health and welfare warning system is to develop the technology which allows for individual pigs to be detected and tracked in a group. The Pig Sustain project, led by Prof Lisa Collins at the University of Leeds, is doing just that. In recently published work authored by Dr Lei Zhang (University of Lincoln), the team show that their setup of CCTV cameras and a custom algorithm using advanced computer vision and machine learning technologies can detect and track pigs with over 97% precision and 95% accuracy. Crucially, the system works without the need to physically mark or tag the pigs, meaning that farmers do not need to change their normal practices to use the technology.
The team are currently expanding their system to work on larger groups of pigs and future plans are to make the algorithm transferable across different pig farming systems (such as on a straw floors).
PigSustain is funded through the Global Food Security’s ‘Resilience of the UK Food System Programme’, with support from BBSRC, ESRC, NERC and Scottish Government.
Zhang, L.; Gray, H.; Ye, X.; Collins, L.; Allinson, N. Automatic Individual Pig Detection and Tracking in Pig Farms. Sensors 2019, 19, 1188.
Full article / DOI can be found here.
Blog
Categories
Archive
- January 2021
- December 2020
- November 2020
- October 2020
- August 2020
- July 2020
- June 2020
- May 2020
- April 2020
- March 2020
- February 2020
- January 2020
- December 2019
- November 2019
- October 2019
- September 2019
- August 2019
- July 2019
- June 2019
- May 2019
- April 2019
- January 2019
- December 2018
- November 2018
- August 2018
- June 2018
- May 2018
- April 2018
- March 2018
- February 2018
- January 2018
- November 2017
- October 2017
- August 2017
- July 2017
- June 2017
- May 2017
- April 2017
- March 2017
- January 2017
- December 2016
- November 2016
- October 2016
- September 2016
- August 2016
- July 2016
- June 2016
- May 2016
- April 2016