Abstract

The integration of big data in livestock management represents a transformative shift towards more efficient, sustainable, and precise farming practices. This paper explores the application of big data analytics in Precision Livestock Farming (PLF), highlighting how real-time data collection and analysis can optimize animal health, productivity, and overall farm management. By leveraging advanced technologies such as sensors, IoT devices, and machine learning algorithms, farmers can monitor critical parameters like feed intake, growth rates, and disease outbreaks with unprecedented accuracy. This data-driven approach enables proactive decision-making, reduces resource waste, and enhances animal welfare, ultimately leading to more sustainable livestock production. The paper also addresses the challenges and opportunities associated with the adoption of big data in the livestock industry, including data integration, privacy concerns, and the need for specialized skills. As the demand for sustainable agriculture grows, the role of big data in Precision Livestock Farming is poised to become increasingly crucial in meeting global food security and environmental goals.