Artificial intelligence in agriculture
Anita Choudhary, Kirti Shekhawat
- Year
- 2024
- Citations
- 3
- Access
- Open access
Abstract
Artificial Intelligence (AI) is revolutionizing agriculture by enhancing efficiency, productivity, and sustainability across various farming practices. AI-driven technologies, including machine learning, computer vision, and robotics, enable precision farming, allowing for real-time monitoring of crops, soil, and environmental conditions. AI algorithms are used to optimize irrigation, fertilization, and pesticide application, significantly reducing resource waste and improving crop yield. Additionally, AI-powered drones and sensors facilitate early detection of plant diseases and pests, while predictive models assist in forecasting weather patterns and market trends, aiding in strategic decision-making. Despite the promising advancements, challenges such as data availability, high costs, and the need for farmer training remain critical to the widespread adoption of AI in agriculture. This paper examines the potential of AI to transform farming practices and discusses the hurdles that need to be addressed for its broader implementation.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002