Artificial Intelligence of Things (AIoT) in Smart Farming: A Bibliometric Analysis and Future Research Agenda

Abstract

Artificial Intelligence of Things (AIoT), which refers to the combination of Artificial Intelligence (AI) and the Internet of Things (IoT), has become an important research area in smart farming. Although the literature on AIoT has expanded rapidly, little is known about its overall development, intellectual structure, and emerging research directions. To bridge this research gap, this paper examines the AIoT literature in smart farming using a bibliometric approach based on publications indexed in the Web of Science Core Collection. Bibliometric techniques, including performance analysis, keyword co-occurrence analysis, and bibliographic coupling, were employed to examine publication trends, most relevant journals in the field, top scholars, countries, institutions, and research themes. The findings show a rapid growth of AIoT research, driven mainly by engineering and computer science disciplines. Five major research themes are identified, covering AI applications in agriculture, IoT-enabled smart farming, intelligent sensing systems, agricultural data management, and prediction models. Based on these findings, the study discusses the evolution of AIoT research, identifies current research gaps, and proposes a future research agenda focusing on artificial intelligence, interoperability, cybersecurity, data quality, technology adoption, sustainability, and responsible innovation. This study provides an extensive overview of AIoT research in smart farming and provides useful directions for researchers and practitioners interested in the future development of digital agriculture.