REVOLUTIONIZING AQUACULTURE THROUGH INTELLIGENT IOT INTEGRATION: A REAL-TIME FISH PRODUCTION DASHBOARD WITH PREDICTIVE ANALYTICS

Abstract

The global aquaculture industry faces challenges in meeting seafood demand sustainably, with traditional monitoring causing up to 30% production losses due to delays and human error. This study presents an innovative Internet of Things ecosystem integrated with Programmable Logic Controller technology for intelligent aquaculture monitoring. A sensor network monitored seven water quality parameters—temperature, pH, dissolved oxygen, Total Suspended Solids, ammonia, humidity, and water level—through PLC-HMI interfaces with real-time cloud connectivity. The system collected 12,692 data points over 30 days with 723ms average API response time and zero errors. Linear regression modeling achieved strong harvest prediction accuracy (R² = 0.80, MAE = 0.43, RMSE = 0.58), tracking fish growth from 10kg to 22kg. Key innovations include industrial-grade PLC-cloud integration, real-time harvest prediction, and automated Telegram alerts. Results demonstrated 40% improved operational efficiency, 85% reduced manual monitoring, and enhanced harvest predictability. This scalable framework offers transformative potential for sustainable, intelligent aquaculture.