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An IoT-Enabled Smart Aquarium System for Real-Time Water Quality Monitoring and Automated Feeding

MD Fatin Ishraque Ayon, Sabrin Nahar, Ataur Rahman, Md. Taslim Arif, Abdul Hasib, A. S. M. Ahsanul Sarkar Akib

TL;DR

This study addresses the challenge of maintaining optimal aquarium water quality by introducing a low-cost ESP32-based IoT system for real-time multi-parameter monitoring (pH, TDS, temperature, turbidity) and automated feeding/oxygenation. The methodology combines edge processing, cloud management via the Blynk platform, and an intelligent alert cooldown to prevent notification fatigue, delivering robust performance in a 10 L testbed with high sensor accuracy and rapid anomaly response. Key contributions include an integrated hardware/software stack, automated feeding and aeration, and a scalable cloud-enabled interface for remote monitoring, reducing manual maintenance. The findings demonstrate that affordable, IoT-enabled solutions can reliably manage aquatic ecosystems for residential and commercial applications, with strong potential for off-grid and AI-augmented enhancements in future work.

Abstract

Maintaining optimal water quality in aquariums is critical for aquatic health but remains challenging due to the need for continuous monitoring of multiple parameters. Traditional manual methods are inefficient, labor-intensive, and prone to human error, often leading to suboptimal aquatic conditions. This paper presents an IoT-based smart aquarium system that addresses these limitations by integrating an ESP32 microcontroller with multiple sensors (pH, TDS, temperature, turbidity) and actuators (servo feeder, water pump) for comprehensive real-time water quality monitoring and automated control. The system architecture incorporates edge processing capabilities, cloud connectivity via Blynk IoT platform, and an intelligent alert mechanism with configurable cooldown periods to prevent notification fatigue. Experimental evaluation in a 10-liter aquarium environment demonstrated the system's effectiveness, achieving 96\% average sensor accuracy and 1.2-second response time for anomaly detection. The automated feeding and water circulation modules maintained 97\% operational reliability throughout extended testing, significantly reducing manual intervention while ensuring stable aquatic conditions. This research demonstrates that cost-effective IoT solutions can revolutionize aquarium maintenance, making aquatic ecosystem management more accessible, reliable, and efficient for both residential and commercial applications.

An IoT-Enabled Smart Aquarium System for Real-Time Water Quality Monitoring and Automated Feeding

TL;DR

This study addresses the challenge of maintaining optimal aquarium water quality by introducing a low-cost ESP32-based IoT system for real-time multi-parameter monitoring (pH, TDS, temperature, turbidity) and automated feeding/oxygenation. The methodology combines edge processing, cloud management via the Blynk platform, and an intelligent alert cooldown to prevent notification fatigue, delivering robust performance in a 10 L testbed with high sensor accuracy and rapid anomaly response. Key contributions include an integrated hardware/software stack, automated feeding and aeration, and a scalable cloud-enabled interface for remote monitoring, reducing manual maintenance. The findings demonstrate that affordable, IoT-enabled solutions can reliably manage aquatic ecosystems for residential and commercial applications, with strong potential for off-grid and AI-augmented enhancements in future work.

Abstract

Maintaining optimal water quality in aquariums is critical for aquatic health but remains challenging due to the need for continuous monitoring of multiple parameters. Traditional manual methods are inefficient, labor-intensive, and prone to human error, often leading to suboptimal aquatic conditions. This paper presents an IoT-based smart aquarium system that addresses these limitations by integrating an ESP32 microcontroller with multiple sensors (pH, TDS, temperature, turbidity) and actuators (servo feeder, water pump) for comprehensive real-time water quality monitoring and automated control. The system architecture incorporates edge processing capabilities, cloud connectivity via Blynk IoT platform, and an intelligent alert mechanism with configurable cooldown periods to prevent notification fatigue. Experimental evaluation in a 10-liter aquarium environment demonstrated the system's effectiveness, achieving 96\% average sensor accuracy and 1.2-second response time for anomaly detection. The automated feeding and water circulation modules maintained 97\% operational reliability throughout extended testing, significantly reducing manual intervention while ensuring stable aquatic conditions. This research demonstrates that cost-effective IoT solutions can revolutionize aquarium maintenance, making aquatic ecosystem management more accessible, reliable, and efficient for both residential and commercial applications.
Paper Structure (14 sections, 5 figures, 4 tables)

This paper contains 14 sections, 5 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Methodology
  4. System Architecture Overview
  5. Hardware Configuration
  6. Sensor Calibration and Data Processing
  7. Control Logic and Alert Management
  8. Software and Communication Stack
  9. Experimental Setup and Results
  10. Experimental Setup
  11. Results and Discussion
  12. Conclusions and Future Work
  13. Conclusion
  14. Future work

Figures (5)

  • Figure 1: System Architecture of the IoT-Enabled Smart Aquarium
  • Figure 2: Control Logic Flowchart of the IoT-Enabled Smart Aquarium
  • Figure 3: Smart Aquarium
  • Figure 4: Blynk Dashboard
  • Figure 5: Web Dashboard