BIG DATA ANALYTICS FOR SMART FARMING.pdf

The rapid advancement of big data analytics is transforming agriculture into a highly data-driven industry, enabling farmers to optimize productivity, sustainability, and profitability. Smart farming integrates multiple technologies such as cloud computing, Internet of Things (IoT), machine learning, and predictive modeling to collect, process, and analyze massive amounts of agricultural data. This paper explores the critical role of big data analytics in smart farming, including its applications in crop monitoring, soil health analysis, yield prediction, pest management, and resource optimization. Drawing from Vedantham (2024) and other recent scholarly sources, the paper also discusses methodologies for data collection and processing, presents real-world case studies, highlights challenges such as data privacy, interoperability, and cost, and identifies future directions in precision agriculture. Tables are provided to illustrate applications, challenges, and comparative tools in big data–driven agriculture. The analysis underscores how big data analytics contributes to addressing global food security while advancing sustainable agricultural practices.