Abstract
The application of artificial intelligence (AI) in agriculture has the potential to revolutionize farming practices, making them more efficient, sustainable, and cost-effective. Neural networks, a subset of machine learning, are increasingly being used in precision farming to optimize crop production, reduce resource usage, and increase yields. This article explores the role of neural networks in precision farming, highlighting their applications in crop monitoring, pest control, irrigation management, and soil analysis. It also examines the benefits of AI-powered solutions for farmers, such as improved decision-making and resource optimization, and discusses the future opportunities and challenges in implementing AI in agriculture.
All articles published in the American Journal of Artificial Intelligence and Neural Networks (AJAINN) are licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
Under this license:
-
Authors retain full copyright of their work.
-
Readers are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) for any purpose, even commercially.
-
Proper credit must be given to the original author(s) and the source, a link to the license must be provided, and any changes made must be indicated.
This open licensing ensures maximum visibility and reusability of research while maintaining author rights.