An Integrated AI and IoT-Based Advisory System for Sustainable Fish Farming_ A Deployed Platform for Small-Scale Aquaculture

Fish farming plays a significant role in ensuring food security and economic sustainability, particularly in developing countries. However, many farmers still rely on traditional practices and lack access to intelligent advisory systems and real-time monitoring tools. This paper presents the Development of a Fish Farming Advisory System Using Artificial Intelligence and IoT, a web-based platform designed to assist fish farmers in decision-making and farm management. The system integrates a Convolutional Neural Network (CNN) model for fish species classification, an AI-based chatbot for farming guidance, and a daily advisory module that provides structured farming instructions. Additionally, an IoT-based water quality monitoring module using an ESP8266 microcontroller with pH and temperature sensors collects real-time pond data and generates automated recommendations to maintain optimal water conditions. A digital marketplace for fish fingerlings is also incorporated to support trading among farmers. Experimental testing demonstrates that the system provides accurate classification results, reliable water quality monitoring, and user-friendly interaction. The proposed platform contributes to improving productivity, reducing manual effort, and promoting sustainable aquaculture through intelligent digital support.