Lameness in dairy cattle is a major health and welfare concern, and perhaps one of the costliest clinical diseases for dairy operations. Timely identification of lameness is necessary to institute early treatment, reduce use of antibiotics, and improve treatment outcomes.
Associate Professor Santosh Pandey, along with veterinary medicine faculty, have been working together to develop an easy-to-use app to identify lameness in cattle at an early stage at the herd level.
“We came up with a prototype software system to automatically detect early signs of cattle lameness using live feeds from mobile smartphone cameras,” Pandey said. “When cattle pass through the camera’s field of view, we can track the different mobility parameters indicative of lameness and its severity. Thereafter, the farm operators are notified about the specific cows needing medical attention.”
Pandey said the whole idea is to make it as easy to use and accessible as possible, where cattle producers can take a video with any type of recording equipment and upload to a data analytics platform to be analyzed to catch lameness earlier, not only saving resources but also improving the cattle’s quality of life.