An IoT-Enabled Smart Aquarium System for Real-Time Water Quality Monitoring and Automated Feeding
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arXiv
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| Autori principali: | , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911371953700864 |
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| author | Ayon, MD Fatin Ishraque Nahar, Sabrin Rahman, Ataur Arif, Md. Taslim Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar |
| author_facet | Ayon, MD Fatin Ishraque Nahar, Sabrin Rahman, Ataur Arif, Md. Taslim Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08484 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An IoT-Enabled Smart Aquarium System for Real-Time Water Quality Monitoring and Automated Feeding Ayon, MD Fatin Ishraque Nahar, Sabrin Rahman, Ataur Arif, Md. Taslim Hasib, Abdul Akib, A. S. M. Ahsanul Sarkar Computer Vision and Pattern Recognition 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. |
| title | An IoT-Enabled Smart Aquarium System for Real-Time Water Quality Monitoring and Automated Feeding |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2601.08484 |