iPond: An IoT-based Water Quality Monitoring System for Fishpond

The cultivation of aquatic species faces a significant Challenge due to water quality degradation, which impacts farming operations and poses a threat to livelihoods. To contribute to the advancement of aquaculture ponds, this study introduces an IoT-based Water Quality Monitoring \System for Fishponds. This system is designed to measure pH and salinity values in real-time, aiming to address the pressing need for continuous monitoring and management of water quality parameters for cultivating milkfish (Chanos chanos). By integrating the prototype with the Blynk IoT system, users can remotely access and control measurements, ensuring that water quality remains within optimal thresholds or 6.5 to 8.5 pH for acidity and 18 to 29 ppt for salinity. In addition, the system is equipped with alert mechanisms to notify users when the parameters exceed predetermined limits promptly. The researchers employed a non-probability purposive sampling technique to assess the functionality, efficiency, and effectiveness of the system in Brgy. Barra, Lucena City. All respondents provided above-average ratings during the evaluation. The prototype received an average functionality score of 4.325 and an efficiency score of 4.13. The error percentages recorded were 0.027% for acidity, 0.187% for salinity, and 4.36% for overall effectiveness. This system enhances cultivation security, enabling farmers to make informed decisions and take timely actions to maintain optimal water quality conditions in fishponds.