Oportunidades de Aplicación de la Inteligencia Artificial para la Optimización de los Procesos de Alimentación y Crecimiento de los Peces en las Unidades Piscícolas del Departamento de Casanare

Abstract

Fish farming in the department of Casanare represents a productive activity with high economic and social potential; however, it faces technical limitations that affect the efficiency of fish feeding and growth processes. This research aimed to identify opportunities for the application of artificial intelligence (AI) to optimize these processes in fish farming units in the region. Methodologically, a mixed, descriptive, and propositional approach was developed through the application of surveys to producers and semi-structured interviews with technicians and sector experts. The results showed that most producers rely on empirical experience for feeding management and keep production records manually, which limits data-based decisionmaking. Recurrent problems were identified related to water quality, feed waste, high input costs, and lack of precision in growth control. Although knowledge about AI is still incipient, fish farmers expressed a positive perception of its potential to improve profitability, reduce losses, and optimize feed conversion. The study concludes that AI can become a strategic tool for strengthening fish farming in Casanare, provided its implementation is accompanied by training processes, technical assistance, and institutional coordination. The proposed strategies focus on the use of intelligent sensors, automated feeding systems, and predictive models based on production data, promoting a transition to fish farming with AI integration.