Automated System of Water Quality Monitoring for Prawn Industry via Labview And Internet of Things

• Published in: International Journal of Intelligent Engineering and Systems
• Main Author: Damanhuri N.S.; Othman M.H.; Othman N.A.; Meng B.C.C.; Abdullah M.H.; Salleh N.A.M.
• Format: Article
• Language: English
• Published: Intelligent Network and Systems Society 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193530510&doi=10.22266%2fijies2024.0630.31&partnerID=40&md5=e53a31191beef45d7c215009d6979ff2

Water quality is crucial to the health of the prawn industry in Malaysia, where unpredictable weather is common. However, many breeders still monitor the water quality manually, which limits their capacity to respond quickly to changing conditions. To address this, an automated system was developed using Internet of Things (IoT) technology to continually monitor and control the pH level and temperature of the saltwater. Sensors are connected to a LabVIEW-equipped data acquisition, and a servo motor operates the probe of the sensors. The proposed system employs ThingSpeak software to display real-time water quality data and has a system of alarms that can be activated to notify the user of any issues. An acid or alkali solution is pumped into the tank using a submersible water pump to regulate the pH level, and a fuzzy logic controller is integrated into the submersible water pump to control the valve for the solutions. From the results, the systems managed to measure the maximum value of the temperature which is 33.86°C meanwhile the minimum value is 30.6 °C. These temperature values are in the desirable range of temperature for prawn which is between 25 °C to 35 °C. Hence, this system depicts that the water is a good temperature for the prawn. Furthermore, the data transfer through wireless via ThingSpeaks’ website is the same as the data transfer through mobile’s app. Hence, this prove that the system is able to deliver the water quality data accurately and can be monitored remotely. The system will greatly benefit the aquaculture industry, and continued development will only improve its effectiveness. © (2024) Intelligent Network and Systems Society.