This research aimed to 1) develop a real-time water quality monitoring and alert application for giant freshwater prawn farming, and 2) reduce mortality rates and increase productivity by utilizing Internet of Things (IoT) technology for continuous water quality measurement. The developed system can measure temperature, pH, and dissolved oxygen (DO) and provides alerts when values fall outside the optimal range. The application was designed to display data in graphical form and deliver notifications via mobile devices. An experimental study was conducted by comparing a traditional pond with an IoT-enabled pond over a period of four months, with 300 prawns in each pond.
        The results showed that the traditional pond had 215 surviving prawns (mortality rate of 28.33%) with a total weight of 1,745.8 grams, while the IoT-enabled pond had 264 surviving prawns (mortality rate of 12%) with a total weight of 2,257.2 grams. The average weight per prawn in the IoT pond was 8.55 grams, compared to 8.12 grams in the traditional pond. Statistical analysis using an Independent Sample t-test indicated a significant difference (p < 0.01).
      The findings confirm that the developed system effectively improves survival rates and productivity in giant freshwater prawn farming and has strong potential for practical adoption in commercial aquaculture.