AGRICULTURAL FIELD MANAGEMENT PROBLEMS: FROM CLASSIC AGRO-TECHNOLOGIES TO ARTIFICIAL INTELLIGENCE

Abstract

The text is straightforward and precise. The agricultural sector has been significantly impacted by artificial intelligence (AI) technologies such as expert systems, natural language processing, speech recognition, and machine vision. This is due to factors such as the rising global population, increasing demand for food, changing weather conditions, and water availability. AI has not only increased the quantity of work in agriculture but also improved its quality. Researchers and scientists are now adopting new IoT technologies in smart farming to enable farmers to use AI technology for the advancement of seeds, crop protection, and fertilizers. This would enhance the financial viability of farmers and contribute to the general economic growth of the nation. AI is being used in three primary areas in agriculture: soil and crop monitoring, predictive analytics, and agricultural robots. Farmers are increasingly using sensors and soil sampling to collect data for farm management systems, which will be utilized for future studies and analysis. This paper enhances the area by doing a study of artificial intelligence applications in the agriculture industry. The text provides an introduction to AI, covering several AI techniques used in the agricultural sector, such as machine learning, the Internet of Things (IoT), expert systems, image processing, and computer vision.