A ConvNet based Real-time Detection and Interpretation of Bovine Disorders

Abstract

The prediction and analysis of bovine diseases like, Bovine Mastitis, Lumpy Skin Disease, Papillomatosis, and Photosensitisation in cattle are highly wanted in the field of animal husbandry. The recent time development in ConvNets has made enormous advances in many fields. This study proposes an effective smart mobile application model constructed based on ConvNet, by image classification using Teachable machine and TensorFlow Lite to recognize four important bovine diseases like, Bovine Mastitis, Lumpy Skin Disease, Papillomatosis and Photosensitisation in the early phases of disease development. It detects bovine diseases with an accuracy of about 98.58%. This mobile application ultimately makes the best partner for the farmers in cattle farming, to detect Bovine diseases expeditiously.