ARTIFICIAL INTELLIGENCE IN FARMING: ADVANCING CROP MANAGEMENT, PEST CONTROL, AND SUSTAINABLE PRACTICES
Keywords:
Artificial Intelligence, Agriculture, Artificial Neural Networks, Machine Learning, Deep Learning, Applications of AI, Fuzzy Systems.Abstract
The integration of Artificial Intelligence (AI) in farming has revolutionized the agricultural sector, transforming traditional practices into precision agriculture. This paper explores the current trends and future scope of AI in farming, highlighting its applications in crop monitoring, yield prediction, disease detection, and automation. Systems are being developed to assist agricultural experts in finding better solutions all over the world. The applications of AI techniques in several fields of agricultural research, industrial insights, and the obstacles to AI adoption in agriculture are the major topics of this study. This paper discusses the benefits of AI-powered farming, including increased efficiency, reduced labor costs, and enhanced decision-making. Additionally, this paper also explores the role of machine learning algorithms, computer vision in collecting and analyzing agricultural data. The paper also addresses the challenges and limitations of implementing AI in farming, such as data privacy, security concerns, and the need for standardization. The analysis reveals that AI has the potential to increase crop yields, reduce environmental impact, and promote sustainable agriculture practices. As the global population continues to grow, AI-powered farming will play a vital role in ensuring food security and meeting the increasing demand for food production.
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