An E-Tag Based Smart Cattle Management And Diagnosis System

Machine learning is a sub field of artificial intelligence which permits forecasting through learning past practices and rules from old information. In this day and age, machine learning is being utilized nearly in any fields, for example, training, medication, veterinary, banking, media transmission, security, and bio-clinical sciences. In human wellbeing, despite the fact that machine learning is commonly favored especially in anticipating sicknesses and recognizing particular danger factors, while there are a set number of distributions where this strategy was applied on veterinary or shows whether it is right and material. Predicting cattle diseases is a well-known problem of interest. Machine learning plays an important role in this regard, to predict the diseases of livestock. This research uses Machine Learning to identify Disease and predict a disease in the e-tag stock at the earliest possible stage with main goals of establishing how early in disease development affected animals can be reliably identified and also to automatically screen animals and alert farmers to those needing treatment, together with developing a protocol for effective use of the trained system. The aim of the proposed study is to develop a system based on providing the best possible information in a timely manner, which is key to making right judgements for farmers and vets alike. It is believed that a system based on e-tagging, together with state-of-the-art machine learning techniques, can provide this efficiency and improvements for larger cattle management companies.