Development and deployment of IOT-based water quality monitoring system for ornamental fish farm at Bendang Man, Sik, Kedah
In fish farming, water quality is important since inadequate water can affect the health and growth of fish. The need for real time and continuous monitoring are crucial to ensure the status of the farm is always in good condition, and appropriate action can be taken if water quality gets polluted....
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
UiTM Press
2025
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/126256/1/126256.pdf https://ir.uitm.edu.my/id/eprint/126256/ https://jeesr.uitm.edu.my |
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| Summary: | In fish farming, water quality is important since inadequate water can affect the health and growth of fish. The need for real time and continuous monitoring are crucial to ensure the status of the farm is always in good condition, and appropriate action can be taken if water quality gets polluted. The work aims to develop a smart IoT system, known as WQMS2 (Water Quality Management System Version 2) to monitor the pH and temperature of fishponds equipped with a notification feature so that users can be notified of any abnormal reading. In this work, pH and temperature were selected as parameters of interest due to their importance in the aquatic life environment. System development which includes calibration and testing, were performed in the laboratory before deploying the system on site for three different locations at the selected fish farm. Thingspeak and Thingsview software were utilised as IoT platforms for smart monitoring system data, while Telegram was used for notification purposes. System performance in laboratory testing, gives a good accuracy of more than 90% with good linearity and hysteresis characteristics. For in situ testing, the system shows a similar pattern as compared to commercial devices with a very small and good distribution of errors. The system was also found to be capable of fetching all the transmitted data with nearly 100% of efficiency for online monitoring. Thus, it can be concluded that the system has been successfully developed and deployed for the meant application. |
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