Photovoltaic-Powered Smart Aquaponic System: Integrating IoT and AI for Sustainable Food Production and Fish Health Management

Aquaponic systems present a promising avenue for sustainable food production. The potential for revolutionizing these systems lies in the convergence of Internet of Things (IoT) and Artificial Intelligence (AI) technologies, enabling real-time monitoring, automated control, and informed decision-making. This paper introduces an innovative photovoltaic-powered smart aquaponic system, driven by a Raspberry Pi microcontroller, equipped with an array of sensors including pH, temperature, turbidity, and ultrasonic sensors dedicated to water level monitoring. The AI algorithms are deployed on the controller to identify fish diseases and estimate fish biomass accurately. A camera module captures images of fish, subsequently subjected to computer vision analysis to detect disease symptoms. Leveraging machine learning models trained on a comprehensive dataset of fish images, the AI system enables timely diagnosis of diseases, thereby facilitating proactive intervention and prevention strategies. Additionally, biomass estimation is conducted utilizing AI-driven image processing techniques, enabling precise evaluation of fish biomass, and facilitating optimization of feeding schedules and growth rate monitoring. For convenient access to system data and controls, a mobile application is developed. Users are furnished with real-time sensor readings, promptly alerted to any detected anomalies or disease outbreaks, and enabled to remotely monitor and control the aquaponic system.