Automation of cattle livestock

An innovative paper called Automation of Cattle Livestock aims to revolutionize the management and care of cattle. The health of cattle and the livelihoods of dependent people are seriously threatened by disease outbreaks, and a lack of veterinary care in a country where cattle are essential to rural economies. In order to improve illness diagnosis, individual cow tracking and food management, this research offers an integrated approach to the automation of cattle livestock management. First, using image processing techniques, a Convolutional Neural Network (CNN)-based system is built for the early diagnosis of lumpy illness in cattle populations. The work makes use of a 700-image collection from Lumpy Skin Image dataset. This approach makes it possible to quickly identify and isolate those that are ill, which reduces the amount of time the disease spreads through out the herd. Second, an RFID technology is used for a productive tracking and identification system is suggested that uses each cow’s unique ID for tracking purpose. This makes it easier to identify and handle every animal in the herd. Furthermore, the system indicates resource usage and nutritional intake by monitoring and controlling feeding item quantities in real-time for cattle and livestock.