ABSTRACT
Big data is a large repository of structured and unstructured information that can be used to build predictive models for better decision making. Big data is sourced through sensors, devices, video/audio, networks, log files, transactional applications, the web, and social media. Most of it is generated in real time and on a very large scale. Besides the government, private sectors such as education, telecoms, healthcare, marketing, and several manufacturing sectors are currently involved in its applications. When used in agriculture, where livestock monitoring devices, drones, and soil sensors provide vast amounts of data to enable automated data-driven farming, the technology has a much broader impact on socio-economic growth. The ultimate goal is to assist farmers, agriculturists, and scientists in implementing good agricultural techniques. The United Nations estimates that the global population will reach 9.8 billion by 2050, a 2.2 billion increase from now, and this means there is a need to step up food crop production. Cultivatable farmland is shrinking due to rapid urbanization and other unethical environmental hazards created by man. It has been identified that agriculture in practice produces huge amounts of raw data with multiple variables and values. Applying this data in the right way can help in cultivating a large amount of produce and ensuring the efficient usage of fertilizer, labour, time, and other vital resources. The application of big data technologies in agriculture can bring a radical shift from the conventional methods of practices in forecasting weather, crop selection, irrigation management, crop diseases and pest management, crop yield prediction, agricultural marketing, and new agricultural policy decision.
