Exploring Machine Learning and IoT Technologies for Disease Detection in Cows: A Systematic Review

The animal farming industry has become a hotspot for research these days. Prioritizing animal welfare is essential due to the crucial role they play in providing dairy products to people. Forecasting cattle health and illnesses in advance is particularly important, considering the potential for animal-to-human disease transmission. Ensuring optimal animal health is vital because humans depend to satisfy their demand for dairy products. Today, numerous Internet of Things (IoT) based technologies are available to keep an eye on the essential health metrics of animals. Besides this, machine learning is being extensively used as a tool for supporting decisions in precise livestock farming. However, an overview of the advancements in IoT and machine learning for precision livestock farming is required, thus a thorough literature analysis has been conducted. This paper’s objective is to give an assessment of the detecting illnesses in cattle using machine learning and the internet of things (IoT) for precision livestock farming and to evaluate the effectiveness of machine learning techniques. The challenges being faced by dairy farmers in application of Smart Farming techniques are also discussed. This Systematic Literature Review study will prove to be beneficial not only for researchers but for dairy farm practitioners also.