Development of Intelligent Anti-Cannibalistic Prototyping for Sustainable Catfish Farming

Abstract

Cannibalism is a major threat that leads to huge losses in catfish farming thereby threatening the sustainability and productivity, among catfish farmers. This study describes the development of a specialized dataset to enhance the development of intelligent anti-cannibalistic IoT prototypes for sustainable catfish farming. The study aims to identify and validate data on specific parameters that affect the cannibalistic behaviour of the African catfish from two perspectives namely: the published metrics, and the practical experiences. To carry out this study, we integrate sensor technologies, and automation to monitor and measure crucial parameters that influence cannibalism within aquaculture environments. The specific parameters include water quality, temperature, dissolved oxygen levels, light intensity, and feeding conditions. Continuous monitoring and measurements of the parameters generated real-time data which is relayed to a centralized control system. Using the dataset would enhance the understanding of behavioral patterns of cannibalism as well as facilitate the creation of IoT solutions that promote sustainable practices. The result of this study demonstrates the potential of data-driven interventions to revolutionize aquaculture, ensuring higher productivity and sustainability.