Water Quality Monitoring in Catfish Pond Using Fuzzy Inference System and Internet of Things

Geographically, Indonesia has a larger water area than its land area. This makes Indonesia have great potential in the water sector, especially in the fisheries sector. One type of freshwater fish that is the most important economic commodity in Indonesia is catfish. However, there are several obstacles in catfish cultivation, especially to maintain good water quality. While water quality is one of the determinants of success during the cultivation process. Some parameters that must be maintained in catfish cultivation are oxygen, temperature, and turbidity to overcome those issues, in this study, we developed a water monitoring and filtration system for catfish ponds. The water parameters (such as oxygen, temperature, and turbidity) were transmitted to an application using Internet of Things technology. In addition, fuzzy inference system using Tsukamoto method was also implemented to the system to set the motor speed automatically for filtration purposes. Based on the result analysis, the system was able to measure the water parameters, to monitor, and to conduct the filtration for catfish ponds. In addition, the implementation of fuzzy logic in this system produced a lower energy consumption cost of 13.7 Wh compared to system without applying fuzzy logic that was advantageous for farmers particularly in the economic perspectives.