Intersection of artificial intelligence in agriculture sector management

摘要

The backbone of India's economy and standard of living is agriculture. More people are employed in India's agriculture sector than in any other industry, according to employment agencies. Under this backdrop, this study investigates the use of artificial intelligence (AI) applications in agriculture, which is frequently thought to be among the most workable solutions to reduce food insecurity and support an expanding population. This study provides an outline of the evolution of AI in research labs and its use in agronomic domains. The investigation starts out by outlining two sectors where artificial intelligence could have a big impact: soil management and weed management. The Internet of Things (IoT), a technology with immense future promise, is then covered. Uneven distribution of mechanization, algorithms’ ability to process massive volumes of data quickly and accurately, and data security and privacy are the three things that need to be fixed before AI-based technology can be extensively used in the market. In particular, the expansion of financial institutions promoting rural development and agriculture depends on NABARD. Appropriate agricultural finance is desperately needed in India in order to help the country's extremely impoverished farmers improve their economic situation. The chapter emphasizes an existing successful research effort and a good potential for application, albeit emphasizing the difficulty of translating machines and algorithms tested in laboratory conditions to real contexts. Agricultural robots targeted at different segments of the agriculture industry have made considerable advancements in the last several years. AI in agriculture has the ability to enhance risk management, crop protection, crop feeding, crop harvesting, market demand analysis, crop breeding, and soil health monitoring. The project's objective is to employ AI to assist by improving current technologies and streamlining both routine and complex tasks. The project will use a digital platform to gather and assess a large amount of data, determine the best course of action, and even kick things off when combined with other technologies.