| Issue |
EPJ Web Conf.
Volume 367, 2026
Fifth International Conference on Robotics, Intelligent Automation and Control Technologies (RIACT 2026)
|
|
|---|---|---|
| Article Number | 03009 | |
| Number of page(s) | 20 | |
| Section | Smart and Sustainable Systems | |
| DOI | https://doi.org/10.1051/epjconf/202636703009 | |
| Published online | 29 April 2026 | |
https://doi.org/10.1051/epjconf/202636703009
IoT-based Automated Water Quality Monitoring System for Fish Hatcheries
1 School of Electronics Engineering, Vellore Institute of Technology, Chennai- 600127, Tamil Nadu, India
2 Principle Scientist, Central Institute of Brackish water Aquaculture (ICAR-CIBA), Santhome, Chennai- 600028, Tamil Nadu, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 29 April 2026
Abstract
Fish health and survival in hatcheries depend heavily on the state of the water. Manual testing is time-consuming and inefficient using conventional techniques. This research suggests a low-cost, IoT-based approach for real-time water quality monitoring and maintenance. To guarantee ideal conditions, the system combines sensors, Raspberry Pi, and AI-based analysis therefore lowering human input and increasing sustainability. Fish health, development, and general sustainability in hatcheries depend on good water quality. Mostly manual, conventional water quality evaluation techniques include regular sample collection and laboratory testing that can be time-consuming, costly, and prone to human mistake. This article presents a low-cost, IoT-based system meant for fish hatcheries' real-time monitoring and proactive maintenance of water quality. The system tracks important criteria including temperature, pH, and total dissolved solids (TDS) by combining a range of sensors. It then gives rapid response on the state of the water environment.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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