Decision System for Reservoir Upwelling Using Fuzzy Logic Based on Internet of Things

Abstract

The lifting of sediments at the bottom of the reservoir caused by vertical currents causes rapid mass mortality of fish. The sediment, which is mostly fish excrement and feed residue, causes the dissolved oxygen (DO) content in the water surface to drop dramatically from the normal value of 3–6 mg / L to below 1 mg / L. This vertical current condition is referred to as upwelling of the reservoir. The occurrence of upwelling in freshwater waters can be predicted from factors of difference in surface temperature and under surface temperatures, DO levels and pH levels. Upwelling will occur if the temperature difference between surface temperature and underwater temperature reaches > 5°C for more than 11 hours. The system for detecting upwelling is built on Internet of Things (IoT) communications by utilizing a fuzzy logic decision system. The reading of data from temperature, DO, and pH sensors is sent to the microcontroller device and delivered to the end user via the Internet network. Fuzzy logic implanted on microcontroller device to get the decision condition is not upwelling, potentially upwelling, and upwelling occurs. Upwelling detection systems are tested in reservoirs and in test environments. From the test results the system successfully read data, process data, and send to users without any data lost or damaged.