Abstract
The application of big data in smart agriculture has significantly enhanced the efficiency and sustainability of agricultural production. Producers can obtain real-time information on soil quality, crop health, and weather conditions by collecting and analyzing large volumes of farming data, enabling more informed decision-making. This data-driven approach optimizes resource use, such as precision fertilization and irrigation, and effectively prevents and addresses agricultural pests and diseases, improving crop yield and quality. However, with the continuous advancement of big data technology, the agricultural sector faces a series of challenges, including data security and privacy protection, data quality and credibility, technical processing issues, and talent cultivation and technology dissemination. This paper will explore the current state of big data applications in smart agriculture, analyze these challenges in-depth, and propose corresponding solutions and future development directions.
