Review Paper on Livestock Health Monitoring and Disease Prediction System Using IoT

Abstract

The integration of Internet of Things (IoT) technology in livestock management has revolutionized traditional farming practices, offering unprecedented opportunities for real-time health monitoring and disease prediction. This review paper examines the current state of IoT-based livestock health monitoring systems, analyzing their components, methodologies, and applications in disease prediction. The paper synthesizes research findings from 2018– 2024, highlighting the effectiveness of sensor networks, data analytics, and machine learning algorithms in early disease detection. Key findings indicate that IoT-enabled systems can reduce livestock mortality by 15–25% and improve overall farm productivity by 20–30%. However, challenges including data privacy, system interoperability, and cost-effectiveness remain significant barriers to widespread adoption. This review provides insights into emerging trends, technological innovations, and future research directions in precision livestock farming.