Integration of AI And Robotics in Precision Agriculture: Enhancing Crop Yield and Resource Efficiency

Abstract

The research focuses on applying artificial intelligence and robotics in precision agriculture to improve farming practices, productivity, and resource usage. The research employs a combination of quantitative and qualitative methods, structured into three phases: The first is analysis and planning, the second one is design and build and the last one is testing and review. AI techniques, machine learning frameworks, and robotic systems were developed and implemented in different agricultural applications including soil identification, plant disease diagnosis, and crop production estimation. Sensor technologies enabled real-time monitoring of the parameters such as moisture content, temperature and nutrient content of the soil which are vital for the efficient use of water and fertilizers. The outcomes reveal a much higher efficiency of applying AI in comparison to traditional methods in terms of accuracy, resource consumption, and crop productivity. The integration strategy allowed to have the effective cooperation between AI systems and robotic parts, and improved decision-making in farming. It focuses on the opportunities of AI & robotics in contemporary agriculture and the necessity of the ethic approach to the technology implementation. The research evidence indicates that the use of the above technologies enhances sustainable use of the resources in farming thus enhancing food security and conserving the environment.