SMART FRAMEWORK FOR COW HEALTH PREDICTION USING BIG DATA WITH DEEP LEARNING BASED IOT ENVIRONMENT

Abstract

The livestock industry is a significant contributor to global food security and economic growth. Ensuring the health and welfare of animals, particularly cows, is essential for sustainable production. This presents a Smart Framework for Cow Health Prediction using Big Data with Deep Learning-Based IoT Environment to address this challenge. The proposed framework integrates the IoT devices, deep learning algorithms, and big data analytics to efficiently monitor, analyse, and predict the health status of cows in real-time. The IoT devices collect a wide range of data, including physiological parameters, behavioural patterns, etc, which are subsequently stored and processed in a big data environment. A deep learning model, incorporating CNN and LSTM networks, is developed to analyse the collected data and predict potential health issues with high accuracy. It includes a user- friendly dashboard for farmers and veterinarians to monitor the health status of cows, receive alerts, and make informed decisions on appropriate interventions. The experimental results show that the proposed Smart Framework improves the prediction accuracy of cow health issues compared to traditional methods.