Monitoring Fish Farming Water Quality with IoT Sensor System

Abstract

Aquaculture is increasingly becoming a vital component of food security and economic sustainability. However, water quality is one of the most critical factors in fish farming that directly affects the health, growth, and productivity of fish. This paper presents an innovative solution that leverages Internet of Things (IoT) technology to create a comprehensive, real-time water quality monitoring system designed specifically for aquaculture. The system integrates various sensors to track crucial water quality parameters such as temperature, pH, turbidity, and total dissolved solids (TDS), thereby ensuring optimal conditions for fish health. By offering continuous monitoring, real-time data analysis, and timely alerts, this IoT-based system enables proactive decision-making, preventing water quality degradation and increasing operational efficiency. This paper also explores the system\'s hardware and software architecture, working methodology, and its implications for the future of sustainable fish farming.

Introduction

This text describes the development of an IoT-based smart water quality monitoring system for aquaculture using an ESP32 microcontroller and multiple sensors.

The system uses hardware components such as an ESP32 microcontroller, temperature sensor (DS18B20), pH sensor (SEN0161), turbidity sensor (SEN0189), and TDS sensor (SEN0244), along with a relay module to control devices like pumps and aerators. These sensors continuously monitor key water quality parameters essential for fish health.

On the software side, the system uses the Arduino IDE for programming and the Blynk application for real-time remote monitoring, visualization, alerts, and control through smartphones or web platforms.

The system works by collecting sensor data, processing it through the ESP32, and sending it via Wi-Fi to the Blynk cloud server. Users can access live water quality data remotely and receive automatic notifications or trigger actions when conditions exceed safe limits. The system also supports data export for long-term analysis.

Conclusion

This IoT-based water quality monitoring system has demonstrated great potential in enhancing the management of fish farming environments. By integrating real-time data collection, remote access, and automated alerts, the system provides fish farmers with a powerful tool to maintain optimal water conditions, ultimately improving fish health and farm productivity. Although there are challenges in sensor maintenance and the complexity of water quality dynamics, ongoing research and technological advancements will continue to refine this system, making it a crucial asset in modern aquaculture.

References

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Copyright

Copyright © 2026 Nikhil Ramteke, Manivesh Singh Nirala, Varsha Kosariya³, , Mitali Telam, Prof. Mukund Kaushal Patel, Dr. Sudha Tiwari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.