IoT-Enabled Automated Aquaponics System for Optimized Water Quality Monitoring and Control

Abstract

Aquaponics is an innovative and sustainable method of food production that combines both aquaculture and hydroponics. However, traditional aquaponics systems require continuous manual monitoring and intervention, which can be inefficient. This paper presents the development of an IoT based automated aquaponics system to optimize water quality management and reduce manual intervention. The system utilized a Nutrient Film Technique (NFT) grow bed with a 1:2 fish tank-to-grow bed ratio, incorporating a 500 L fish tank for 25 fish and a 1 m² grow bed for 48 plants. A filtration unit converted fish waste into nutrients, while a pump (2.7 m head height) and actuators regulated pH, temperature, electric conductivity (EC), and dissolved oxygen (DO). IoT sensors continuously monitored water quality, with a PIC microcontroller transmitting real-time data via a GSM module to the ThingSpeak cloud. Automated controls, including solenoid valves and aerators, adjusted conditions based on predefined thresholds, with alerts sent to users for abnormal values. Over three months, the system maintained optimal water quality (DO >5.5 mg/L, pH 6.5-7.5, temperature 22-32°C, EC <2 dS/cm), ensuring stable fish and plant growth. The system yielded 5.198 kg of fish and 9.57 kg of plants, demonstrating improved water efficiency, reduced human error, and enhanced growth synchronization. This scalable system offers a promising approach to sustainable aquaponics and resource-efficient agriculture. The results demonstrate the effectiveness of the proposed system in optimizing aquaponics operations and ensuring sustainable agricultural practices. Incorporating renewable energy sources, AI based predictive analytics and advanced sensor network will improve the scalability and real time decision making.