Published Paper Details:

Smart Farming Using Technology Agriculture is recognized as an important field with significant economic impacts in some countries. Due to large population growth, meeting people's nutritional needs has become an important issue. To achieve these food security goals, the transition to smart agriculture has become inevitable. Smart farming is a new approach to agriculture that uses the power of machine learning and technology to increase productivity, sustainability, and operational efficiency. This article explores the use of machine learning in smart farming to improve many aspects of agriculture. We discussed how machine learning algorithms can be used for crop monitoring, yield prediction, disease diagnosis, and resource management. Integration of data from sensors, drones, satellites, and other sources allows farmers to make instant data-driven decisions. These concepts also highlight the benefits of smart agriculture, such as increased yields, reduced resource waste and increased sustainability. Additionally, we discuss the challenges and limitations of machine learning in agriculture and provide insight into the future of smart agriculture, which promises to transform the way we produce food and manage agriculture.