Real-Time Data Pipeline for Livestock Health Monitoring

As a startup in the Livestock & Dairy industry, we recognize the critical need for real-time health monitoring of livestock to enhance productivity and reduce losses. We propose developing a robust data pipeline that efficiently collects, processes, and analyzes real-time data from IoT sensors placed on cattle. The project will leverage Apache Kafka for real-time event streaming, Spark for processing large data sets, and Airflow for orchestrating data workflows. Our goal is to identify health trends and irregularities early, allowing farmers to take proactive measures. The data will be stored in Snowflake for scalable analytics, and dbt will be used for transforming and modeling the data. This infrastructure will enable the integration of MLOps for predictive analytics in the future, ensuring that our solution remains at the forefront of technological advancement. By deploying this pipeline, we aim to improve livestock health management and overall dairy production efficiency.