Machine Learning and Image Processing Based Approach for Improving Milk Production and Cattle Livestock Management

Abstract

Dairy products are popularly consumed around the globe since it provides a rich source of vitamins and minerals essential for maintaining human health. Developing countries have grown their proportion of global dairy production in Sri Lanka Cattle Livestock is one of the most prospective subsectors of agriculture in Sri Lanka. Demand for quality milk products in Sri Lanka have especially increased in the recent past due to restrictions in importing dairy products.Under such circumstances cattle farmers are much encouraged to improve their milk production. However, there are many challenges in improving milk production by farmers. These include challenges in identifying breeds of cows for milk production inability of identifying diseases and conditions of farm animals hindering milk production and forecasting milk production of a farm.This research used a machine learning and image processing to identify parasite disease and heat stress of cows hindering milk production and identify breeds capable of producing quality milk. In addition, it will also use machine learning to predict heat stress level of cattle, identifying the breed types, identification of parasitic species and risk level.The machine learning model was generated with higher accuracy