Kalman filter-based data stabilization for an automated water quality monitoring system in Macrobrachium Rosenbergii larvae culture / A. Y. Yaakob, M. H. Azham and M. H. M. Ramli

• Main Authors: Yaakob, A. Y., Azham, M. H., M. Ramli, M. H.
• Format: Article
• Language: English
• Published: UiTM Press 2024
• Subjects: Qualities of water. Water quality
• Online Access: https://ir.uitm.edu.my/id/eprint/105983/1/105983.pdf; https://ir.uitm.edu.my/id/eprint/105983/

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.