Abstract:
The aquaculture industry's success hinges on maintaining optimal water quality,
especially for fish breeding. This study aims to optimize aquaculture practices through
an IoT-enabled water quality monitoring system. By integrating advanced sensors like
temperature, pH, and TDS, the system allows real-time monitoring of critical
parameters
This
proposed framework applied Arduino innovation and
NodeMcuESP8266 as the microprocessors. The gathered data is accessible through a
user-friendly interface, providing valuable insights in to water quality trends.
Furthermore, the obtained data is sent to the IoT based Blynk application to monitor the
quality of the water through android mobile phone. When the water quality parameters
in out of range, system will trigger a SMS alert using GSM module (SIM800L).
Additionally, collected data is analysed using random forest regression models to
predict water quality fluctuations and optimize breeding environments. This research
aims to propel aquaculture enterprises towards unprecedented levels of efficiency,
sustainability, and breeding success in harmony with aquatic ecosystems.
