INNOVATIVE APPROACHES TO THE MANAGEMENT OF AGRONOMIC PROCESSES USING ROBOTICS AND ARTIFICIAL INTELLIGENCE

Abstract

The integration of robotics and artificial intelligence (AI) in agriculture represents a transformative step in managing agronomic processes, unlocking potential for increased productivity, sustainability, and precision. This direction is relevant due to the rising global food demand, the need for more efficient resource use, and the environmental challenges faced by traditional agricultural methods. Conventional farming methods often lead to inefficient resource use, high labor costs, and suboptimal yields, making advanced technologies such as robotics and AI crucial for addressing these issues. The purpose of this study is to explore innovative solutions in agronomic process management through the integration of robotics and AI, with a focus on their role in optimizing crop production, reducing waste, and enhancing the accuracy of agricultural practices. The results of applying robotics and AI in agriculture demonstrate the potential of this approach. Autonomous robots equipped with sensors and AI algorithms can monitor soil conditions, detect pests, and assess plant health in real-time, enabling targeted adjustments. AI-based systems, using machine learning and predictive analytics, can optimize irrigation schedules, fertilizer use, and pest control strategies, leading to more efficient resource use and higher crop yields. AI-powered drones and robots have shown the capability to perform tasks faster and with greater accuracy than traditional methods, helping reduce costs and increase productivity. Thus, the innovative use of robotics and AI in agronomic process management is reshaping agriculture. These technologies not only improve the efficiency of agricultural operations but also pave the way for sustainable farming, reducing resource consumption and minimizing environmental impact.