A Flexible Water Monitoring System for Pond Aquaculture
Issued Date
2022-01-01
Resource Type
Scopus ID
2-s2.0-85137735549
Journal Title
International Conference on Digital Government Technology and Innovation, DGTi-Con 2022 - Proceedings
Start Page
91
End Page
95
Rights Holder(s)
SCOPUS
Bibliographic Citation
International Conference on Digital Government Technology and Innovation, DGTi-Con 2022 - Proceedings (2022) , 91-95
Suggested Citation
Wannee N., Samanchuen T. A Flexible Water Monitoring System for Pond Aquaculture. International Conference on Digital Government Technology and Innovation, DGTi-Con 2022 - Proceedings (2022) , 91-95. 95. doi:10.1109/DGTi-CON53875.2022.9849186 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/84367
Title
A Flexible Water Monitoring System for Pond Aquaculture
Author(s)
Author's Affiliation
Other Contributor(s)
Abstract
Water quality is the most important factor for pond aquaculture. Farmers must be able to control a water quality to be within the appropriate range for each kind of aquatic animal, which needs both skill and knowledge. This work proposes a flexible water quality monitoring system for pond aquaculture, which can be configured to fit with a particular aquatic animal. Three types of sensors are applied to measure the water quality including pH, temperature, and dissolved oxygen sensors with 2 types of wireless connection, i.e., WiFi and NB-IoT. A microcontroller is used to process these sensing signals and send data to a cloud server. The system monitors the water quality all the time. If the water quality is not within the controlled range, the alert message will be sent to the farmers. The dashboard is also provided for real-time system monitoring. Systems can be selected as three kinds of aquatic animals including white shrimp, white sea bass, and tilapia. The controlled range will be changed according to the type of aquatic animal that the user selected. As the result, we found that the proposed system can perform as designed and the accuracies of the prototype are 98.5%, 97.6%, and 95.1% for pH, temperature, and dissolved oxygen, respectively, when compared with the standard tools. The proposed system can support both connections, i.e., WiFi and NB-IoT.