Technology for earlier diagnosis of serious cattle disease

Monitoring dairy calves with precision Internet of Things (IoT)-based technologies leads to earlier diagnosis of calf-killing bovine respiratory disease (BRD), according to research from three US universities. Researchers from Penn State University, the University of Kentucky and the University of Vermont say the findings offer dairy producers an opportunity to improve farm economics. Melissa Cantor, assistant professor in Penn State’s College of Agricultural Sciences, said IoT, with its embedded devices equipped with sensors, processing and communication capabilities, software and other technologies to connect and share data with other devices over the internet, allows farmers to closely monitor and analyse calf conditions. IoT generates a huge amount of data, so to make it easier to understand and prove calf health problems, the researchers used machine learning – a branch of artificial intelligence that learns the hidden patterns in the data to distinguish between sick and healthy calves. “We put leg bands on the calves, which record data on the activity behaviour of dairy cattle, such as the number of steps and time spent lying down. And we used automatic feeders that dispense milk and grain and record feeding behaviour, such as the number of visits and litres of milk consumed. Information from these sources signalled when a calf’s condition was about to deteriorate”. In the study of 159 dairy calves, the system achieved exceptional accuracy in identifying sick and healthy calves, predicting 70% of sick calves 4 days before the actual diagnosis and 80% of calves that developed chronic disease within the first 5 days of illness.