Big Data Concept

  Introduction Agriculture faces the challenge of feeding a growing global population, projected to reach 9.7 billion by 2050, while addressing climate change and resource constraints. Big Data analytics, powered by sensor and satellite data, is revolutionizing agriculture by enabling precise crop yield predictions and optimized farming practices. By integrating diverse data sources, such as soil sensors, weather data, and satellite imagery, farmers can make data-driven decisions to enhance productivity and sustainability. This chapter explores how Big Data supports crop yield prediction, detailing methodologies, applications, challenges, and future trends in smart agriculture. The Role of Big Data in Agriculture Big Data analytics processes vast, complex datasets to uncover insights that improve agricultural outcomes. In crop yield prediction, it leverages real-time and historical data to forecast yields, optimize resource use, and mitigate risks. Key Characteristics of Big Dat...

  Introduction Have you ever wondered how modern technology is transforming traditional farming practices? Consider this: IoT-connected devices in agriculture are projected to generate over 75 million data points daily by 2025. This enormous influx of data, coupled with Big Data analytics, is revolutionizing agriculture, making it more efficient, sustainable, and productive. The integration of IoT and Big Data provides farmers with insights into weather patterns, soil conditions, and crop health, enabling them to make informed decisions and optimize resource use. This article explores the critical role of Big Data in IoT-driven agriculture, highlighting its benefits, practical applications, and future potential. Body Section 1: Background and Context The agricultural sector has traditionally relied on manual processes and historical data to make decisions. However, the advent of IoT and Big Data is changing this landscape. IoT refers to the network of physical objects embedded w...