Smart Aquaculture: IoT-Enabled Monitoring and Management of Water Quality for Mahseer Fish Farming

Abstract

Aquaculture is essential for meeting the growing global demand for seafood by cultivating aquatic species in controlled environments such as ponds and tanks. This study presents an innovative IoT-based water quality monitoring system designed specifically for Mahseer fish farming. The system utilizes an ESP32 Development Board equipped with sensors to monitor water quality parameters and employs the Blynk 2.0 platform for real-time data visualization. A C/C++ algorithm managed through the Arduino IDE facilitates effective communication between the sensors and the microcontroller. The results demonstrate the system's effectiveness in maintaining optimal water conditions, enabling early detection and timely intervention for potential issues. This approach enhances the sustainability and efficiency of Mahseer fish farming. Future research will focus on refining accuracy, improving scalability, and integrating advanced data analytics to boost predictive capabilities and promote more efficient and profitable aquaculture practices.