Smart Fisheries: Real-Time Water Quality Management and Automated Feeding System Design for Tilapia Farming using ESP32 Micro Controller - Yudistira, Bagus Gede Krishna; Hapsari, Cindy; Adnyana, Gede Defry Widhi; Nath, Wiswa; Putra, I Putu Romyadhy Maha (Journal of Artificial Intelligence and Software Engineering, 2025)
The fisheries sector in Jinengdalem Village, Buleleng, Bali holds considerable potential but continues to face challenges related to operational efficiency and unstable production outcomes. This study proposes an innovative solution through Smart Fisheries: The AI-Powered IoT in Smart Fisheries, an intelligent aquaculture system powered by Artificial Intelligence (AI) and the Internet of Things (IoT). The system is designed to perform real-time monitoring of water parameters, automate feeding processes, and analyze fish growth in order to enhance aquaculture productivity and sustainability. The research methodology follows a Research and Development (RD) framework, utilizing the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). Preliminary results indicate that the system provides accurate environmental data and supports data-driven decision-making in fishery management. This project is expected to serve as a replicable model for implementing digital aquaculture technologies in similar regions.