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.
Arivarasi et al. (2026) studied this question.