Identification of Farm Animals’ Diseases: Revolution for 21st Century Farming and Agriculture 5.0 in South Asian Region

It has been 21st century and we have seemed an agricultural paradigm shift in the combination of new technologies and bringing the rise of the Agriculture 5.0, i.e. a data driven, automated and precision focused techniques. The early and accurate diagnosis in farm animals is the core concept of such a revolutionary scenario, whose provide the efficient and accurate livestock output, food security and reduction of costs. This study examines how the modern technologies such artificial intelligence (AI), Internet of Things (IoT), machine learning, and image processing can be used in identification of the disease across the South Asia region with proper cure for the disease. The work proposes a cost effective, reliable and scalable disease detection based on the analysis of the veterinary records, sensor data in real-time and image diagnostics, which will be better in the socio economic and infrastructural setting of the South Asia. The result present significant improvements in diagnostic accuracy, early detection and cure recommendation for the overall animal health management. This paper concludes that, how digital disease identification system can be revolutionized to promote the sustainable agriculture, and more importantly move the gap between the traditional and technological advancement in the area of the agriculture. This Paper presents a machine learning application that is going to classify and identify diseases in farm animals using clinical symptoms, image feeds and previous health history automatically. The model is trained with various types of diseases that are common in the South Asian area and applies supervised learning algorithms to offer high-diagnostic accuracy, including the Random Forest, Support Vector Machines, YOLO and Convolutional Neural Networks.