AI-enabled Crop Health Monitoring and Nutrient Management in Smart Agriculture

The rapid advancement of artificial intelligence (AI) has paved the way for transformative applications in various fields, and agriculture is no exception. In this research paper, we explore the integration of AI technologies in smart agriculture to enhance crop health monitoring and nutrient management. By leveraging AI algorithms and techniques, we aim to improve the efficiency and sustainability of farming practices. The paper delves into the utilization of AI for early detection of crop diseases and pests, as well as the development of predictive models for precise nutrient management. Remote sensing and imaging technologies play a crucial role in real-time monitoring, allowing for informed decision-making. Through a series of case studies and evaluations, we demonstrate the effectiveness and potential benefits of AI-enabled crop health monitoring and nutrient management in modern agriculture. Despite the promising results, challenges and limitations are discussed, and future directions for research and application are suggested.