Smart Livestock Farming Framework for Real-Time Behavioral Monitoring and Epidemic Prevention

Abstract

Smart livestock production is a smart and viable solution to enhance health tracking of the animals, farm production, and avoidance of epidemic outbreak with the latest sensing and machine learning technologies. The common livestock observation techniques have relied on manual observation and regular veterinary check-ups that are usually insufficient in identifying abnormal behaviors and signs of illness in the animal early enough. In order to overcome these shortcomings, the present paper will suggest an IoT-based smart livestock farming system combined with a Random Forest classification tool to implement real-time behavioral tracking and prevent epidemics. The suggested model utilizes wearable and environmental sensors to continuously gather information about livestock behavior and physiological processes, such as body temperature and activity during movement, feeding habits, resting time, and environmental factors. The sensor data obtained are analyzed on an intelligent analytical platform that includes preprocessing, feature extraction and classification-based prediction of diseases. Random Forest algorithm is used to distinguish between livestock health conditions and possible risk of epidemic based on abnormalities in their behaviors and differences in physiology. The effectiveness of the proposed framework is assessed on standard classification measures like Accuracy, Precision, Recall, and F1-score, which show excellent predictive power and good performance in detecting the disease. The experimental analysis shows that the proposed system dramatically enhances the efficiency of the real-time monitoring system, minimises the number of manual interventions, allows early prevention of epidemics, and contributes to making smart decisions in order to manage livestock sustainability. Combining IoT sensing and behavioral analytics implemented through the Random Forest is a viable and scalable solution to accurate livestock farming and advanced animal health systems.