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Data Engineering for Smart Farming Building Scalable Agri-Data Pipelines
Abstract
Smart farming is revolutionizing agriculture by leveraging data-driven insights to optimize crop yields, resource usage, and operational efficiency. However, the success of smart farming initiatives heavily depends on the design and implementation of scalable, robust agri-data pipelines. This chapter explores the critical role of data engineering in modern agriculture, focusing on techniques for collecting, processing, and managing vast volumes of heterogeneous agricultural data. We discuss the integration of IoT sensors, drones, satellite imagery, and weather stations, along with methods to handle challenges like data heterogeneity, real-time ingestion, data quality, and storage scalability. The chapter also presents architectural patterns for building end-to-end agri-data platforms, including the use of cloud-native solutions, edge computing, and AI-driven analytics pipelines.
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