A Review on IoT and Machine Learning Approaches for Cattle Health Prediction in Precision Livestock Farming

Abstract

The livestock farming industry has turned into a focal point for research nowadays. Particularly, the animal health conditions are of utmost importance because the human beings are dependent on animals in order to fulfil their requirements of dairy products and meat. Instead of reacting to diseases after their outbreak, the modern technologies present a possibility for monitoring the key health parameters of animals on a regular basis such as amount of food and fluids consumed, movement, body condition score etc. By collecting this information and applying advanced artificial intelligence and machine learning, the farmers can recognize, foresee and avert the outbreak of animal diseases, which can aid them in better decision making and perform timely interventions. A review of the literature on the use of Internet of Things and machine learning based systems to predict the health status of cattle by measuring their health parameters using different types of sensors and other wearable technologies for precision livestock farming is presented in this study.