Alen Alempijevic, roboticist and senior lecturer at the University of Technology, Sydney is developing a tool that uses 3D imaging and artificial intelligence to accurately measure the condition of an animal so that farmers can better manage their livestock.\nAn article published this week in UTS's Brink magazine said that affordable sensors capture images of a cow at 30 frames per second as it enters a \u2018crush\u2019 or a cage for examination. 3D images relay fat and muscle content in the cow, which is then analysed to give the animal a condition score.\nExpert cattle assessors helped grade fat and muscle, looking at different shapes of the cow\u2019s body parts. Those shapes were assigned mathematical descriptions to train a machine to estimate a cow\u2019s condition. The machine is able to \u201csee\u201d the 3D shape and make judgements on the condition.\n\u201cEssentially we are enabling computers to think and reason about what they see,\u201d Alempijevic said in Brink.\nBy being much more certain about an animal\u2019s condition, farmers are able to better form their feeding regimes or breeding programs, he said.\n\u201cThis technology will help farmers with management of breeding \u2013 using genetic traits to select the next generation," he said. It will minimise non-compliance, and help farmers decide if an animal needs more time on grass or is ready to be slaughtered, he said.\nDr Alex Ball, general manager of livestock production at Meat and Livestock Australia, told Brink that predicting yield in live animals is the holy grail in the industry.\n"At the moment we rely on poor information from a range of different measures \u2026 and accuracy is as low as 20 to 30 per cent. This technology would mean a transformative shift in livestock management with accuracy as high as 80 to 90 per cent,\u201d he said.\nRead: Farming the smart way\nThe tool also helps ensure farmers not only grow the strongest livestock they possibly can but are meeting industry standards. Non-compliance with Meat Standards Australia\u2019s grid, for example, can result in loss of $300 per animal, Brink reported.\nAlempijevic is starting to apply his tool to sheep. \u201cAnd it\u2019s not just the livestock industry, it\u2019s in general \u2013 robotics and the integration of sensing and artificial intelligence will help us bridge this gap between consumer demand and the producer,\u201d he said.\nHe said fast and accurate RGB-D sensors only became affordable within the past few years, which is what spurred on the research.\nAlempijevic also grew up in a farm for most of his teenage years when his parents moved him and his brother back to their home country Serbia during the 1980s. His brother stayed on the farm and he returned to Sydney, where he was born, to study.\nMeat and Livestock Australia is funding the project, and it is expected to be out to market by 2017.