| Summary: | Manual monitoring and management of water quality parameters in Macrobrachium Rosenbergii (freshwater prawn) larval culture are labour-intensive, time-consuming, and susceptible to human error. This research aims to develop and evaluate an automated water quality monitoring system for freshwater prawn larval culture, with a specific emphasis on data stabilization. An ESP32 microcontroller is implemented to allow remote communication using an internet connection. The system continuously monitors critical parameters using sensors such as temperature, pH, turbidity, and Total Dissolved Solids (TDS), facilitating remote real-time data acquisition. The Message Queuing Telemetry Transport (MQTT) publish-subscribe protocol is employed for seamless communication between the microcontroller and the monitoring dashboard. A Kalman filter is integrated into the system, enabling real-time sensor noise reduction and dynamic adaptation to changes. The filtered data are displayed remotely using a Node-RED dashboard with graphical representations. The implementation of the ESP32 microcontroller with the MQTT protocol and Node-RED has proven to be a robust platform for seamless data communication and presentation. Integration of the Kalman Filter significantly mitigates fluctuations in sensor readings. This is further proven by comparisons of the filtered data with known-good sensors, which have shown minimal to acceptable error percentages between 1% - 8.5%, where the error can mainly be attributed to environmental factors. Overall, this study has established a framework that can contribute to improving aquaculture practices and promoting environmental sustainability in freshwater prawn culture operations. The validated system provides valuable insights that assist farmers in facilitating a more efficient prawn culture operation. © (2024), (UiTM Press). All rights reserved.
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