Media-Based Aquaponics Using IoT Components for Smart Agriculture

Abstract

Ensuring optimal water quality is essential for efficient aquaculture and aquaponics management. This paper presents an IoT-based intelligent monitoring system that integrates Edge Computing (Raspberry Pi 4 Model B) and Fog Computing (ESP32) for real-time water quality analysis and control. The system utilizes pH, TDS, temperature, and turbidity sensors to monitor water conditions, while air pumps, water pumps, solenoid valves, servo motors, buzzers, and thermoelectric Peltier systems regulate environmental factors. The Edge Computing unit preprocesses data and applies lightweight machine learning models, while the Fog Computing layer transmits refined data to the cloud for remote monitoring and analytics. The proposed solution enhances water management efficiency, reduces manual intervention, and ensures optimal aquatic conditions for sustainable fish farming and plant growth.