Conception et développement d’un système intelligent de contrôle de la qualité de l’eau et de traçabilité des produits aquacoles : cas de tilapia rouge (oreochromis spp.)

Abstract

This study examines the integration of Internet of Things (IoT) and artificial intelligence (AI) technologies in aquaculture, aiming to optimize breeding conditions, ensure sustainable management of natural resources, and improve the economic and environmental viability of aquaculture systems. The main objective is to provide aquaculturists with tools that allow for improved farm management and better traceability of the supply chain. The experiment, conducted at the experimental station of the CNRDPA in Ouricia (Sétif), consisted of regular monitoring of water quality thru two essential physicochemical parameters: temperature and pH. These parameters were measured manually and using an IoT system ensuring real-time data collection. The results show a strong correlation between the two measurement methods, with temperatures ranging between 20 °C and 26 °C, and a pH between 7.17 and 8.19, despite slight variations due to imperfect calibration of the pH sensor. The collected data was correlated with key zootechnical indicators, notably the specific growth rate (SGR) and the feed conversion ratio (FCR). It turns out that water quality is a determining factor for the health and growth of fish. Optimal control of temperature, pH, dissolved oxygen, and ammonia improves nutrient assimilation, resulting in a reduced FCR and a high SGR.