“One potential benefit of using AI for livestock health monitoring is the ability to monitor large numbers of animals in real-time.”, says Bhusan Chettri. The ability of AI-based systems to provide real-time data on the animals' health allows for early detection and intervention of any health issues, which can ultimately lead to better animal welfare, prevent the spread of diseases and promote higher quality of produce. Additionally, AI-based systems can provide more detailed and accurate information than traditional methods, as they can analyse data from multiple sources and apply advanced algorithms to identify patterns and make predictions. Furthermore, automatic systems can help with the identification of patterns and trends in the animals' health, allowing for more effective preventative measures. In contrast to AI-based approaches, traditional methods for monitoring livestock health often rely on manual observation and interpretation by trained personnel. While these methods can be effective, they can be time-consuming and labor-intensive, and may not be able to keep pace with the large number of animals on many modern farms. One of the major advantages of using AI for livestock health monitoring is its ability to process large amounts of data quickly and accurately. This allows farmers to monitor the health of their animals in real-time, and to detect potential issues before they become serious. Additionally, because AI algorithms can be trained to recognize specific patterns and trends, they can be highly accurate in detecting health issues that may be difficult for humans to identify.