Modern approaches to intelligent automation of agricultural technological processes based on artificial intelligence

Abstract

Modern agriculture faces critical challenges related to efficient resource management, climate resilience, and productivity growth. These challenges are increasingly being addressed through artificial intelligence (AI)-based technologies. This article analyzes modern approaches to intelligent automation of agricultural technological processes using AI within the context of digital agriculture development in Uzbekistan. The study examines AI-driven solutions for irrigation management, crop monitoring, early disease detection, and yield prediction. Deep learning techniques applied to drone and satellite imagery enable accurate assessment of crop vegetation conditions, while AI systems integrated with IoT sensors optimize water and fertilizer consumption. In addition, expert systems provide real-time, data-driven recommendations to farmers. Experimental studies conducted in different agricultural regions of Uzbekistan demonstrate that AI-based intelligent systems significantly reduce resource consumption while maintaining stable crop yields. The results confirm that artificial intelligence is a key technological driver for sustainable and competitive agricultural development.