Smart Farm Research in Korea (2015-2024): Trends and Thematic Evolution from an Engineering and ICT-Centered Perspective

This study used bibliometric methods to analyze Korean smart farm research from 2015-2024, examining 730 articles across two periods: 2015-2019 and 2020-2024. Korean smart farm research showed rapid growth with a 47.8% compound annual growth rate. Engineering dominated with 49.9% of publications, while IT-related journals comprised 66.7% of top journals, confirming its technology-focused and engineering-driven nature. Regional flagship national universities led research as central hubs, with growing industry-academia-research collaborations. Keyword analysis revealed explosive growth in AI-related terms including AI, Deep Learning, and Machine Learning, confirming AI technology's expanding influence. Thematic cluster analysis identified 11 research clusters within an integrated smart farm technology ecosystem, including precision agriculture, environmental monitoring, next-generation facilities, and predictive analytics. Thematic evolution showed a paradigm shift from Period 1's basic hardware and ICT convergence focus to Period 2's emphasis on AI-based applications, technology commercialization, urban agriculture, food security, and social problem-solving. The study recommends strengthening industry-academia-research ecosystems, expanding international cooperation, advancing AI-based convergence research, and expanding technology acceptance and commercialization research to activate Korean smart farm research.