Abstract
This paper examines the integration of human factors, artificial intelligence (AI), and automation in U.S. smart farming, focusing on sustainability and safety management. The agricultural sector is witnessing rapid transformations driven by AI and automation technologies, which are applied in crop management, soil monitoring, and livestock operations. These advancements promise significant improvements in productivity and environmental sustainability. However, their success heavily depends on the human dimension—specifically, the effective incorporation of human factors to ensure technology adoption, usability, and safety. By highlighting key innovations in smart farming, such as robotic milking, automated phenotyping, and safety systems, the paper underscores the importance of a synergistic approach that aligns technological solutions with human needs. The study also addresses challenges such as resistance to technological change, training requirements, and the potential risks of automation. Finally, it presents case studies demonstrating how AI-driven solutions can enhance operational safety and sustainability while calling for continuous research into the human factors shaping agricultural innovation.
Keywords
Smart Farming, Human Factors, Artificial Intelligence (AI), Automation, Sustainable Agriculture, Safety Management
Full Text
This paper examines the integration of human factors, artificial intelligence (AI), and automation in U.S. smart farming, focusing on sustainability and safety management. The agricultural sector is witnessing rapid transformations driven by AI and automation technologies, which are applied in crop management, soil monitoring, and livestock operations. These advancements promise significant improvements in productivity and environmental sustainability. However, their success heavily depends on the human dimension—specifically, the effective incorporation of human factors to ensure technology adoption, usability, and safety. By highlighting key innovations in smart farming, such as robotic milking, automated phenotyping, and safety systems, the paper underscores the importance of a synergistic approach that aligns technological solutions with human needs. The study also addresses challenges such as resistance to technological change, training requirements, and the potential risks of automation. Finally, it presents case studies demonstrating how AI-driven solutions can enhance operational safety and sustainability while calling for continuous research into the human factors shaping agricultural innovation.