Performance Evaluation of River Water Quality Monitoring Using Lora Connectivity with Fuzzy Algorithm
AbstractThis study was proposed a river water quality monitoring application, connected by sensors such as pH, turbidity and Total Dissolved Solids (TDS) sensor to measure acidity, turbidity levels and amount of dissolved solids, respectively, as well as reduce bad effect of polluted river water. This river water quality monitoring tool was able to process input data from sensors using fuzzy algorithms and determine whether the river water quality is good or not. LoRa functions as data transmission communication and Antares as a cloud service to store data obtained from sensors. Furthermore, data obtained was displayed in the Smartphone Android application. The rivers that were tested are located in Citarum river sector 6 and 21. The results showed that the accuracy of the temperature, TDS and pH sensor were 98.69%, 89.69% and 99.39%, respectively. Furthermore, the average value of RSSI Citarum sector 6 and 21 were -111,576 dB and -112,855 dB, respectively. Meanwhile The average SNR of Sector 6 was -6,46 dB and Citarum sector 21 was -12,85851 dB.
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