Sharon A. Bucalon Lyndon A. Rosas
The rapid integration of digital technologies has transformed aquaculture into a data-driven industry, yet the expanding body of research on smart technologies remains fragmented across multiple scientific disciplines. Despite increasing interest in intelligent aquaculture systems, a comprehensive understanding of the field's global development, knowledge structure, and emerging research directions remains limited. This study addresses this gap through a bibliometric analysis of 7,197 English-language publications indexed in the Scopus database from 1976 to 2026. Bibliographic data were analyzed using the Bibliometrix package in RStudio and VOSviewer to evaluate scientific growth, research productivity, collaboration networks, conceptual structure, thematic evolution, and future research directions. The results reveal accelerated scientific expansion over the past decade, driven by a relatively concentrated group of influential journals, researchers, institutions, and countries, with China emerging as the leading contributor to both scientific production and international collaboration. Collaboration network analysis demonstrates an increasingly interconnected global research community, while keyword co-occurrence and thematic evolution analyses reveal a clear transition from sensor-based environmental monitoring toward integrated applications of the Internet of Things, artificial intelligence, machine learning, computer vision, and remote sensing for intelligent aquaculture management. Emerging themes further indicate growing attention to sustainability, predictive analytics, and autonomous decision-support systems. By synthesizing nearly five decades of scientific development, this study provides a comprehensive knowledge map of smart aquaculture research, identifies strategic research opportunities, and offers evidence-based guidance for researchers, policymakers, and technology developers advancing sustainable digital transformation within the global aquaculture sector.