Analysis and Implementation Monitoring Flood System Based on IoT Using Sugeno Fuzzy Logic

Abstract

Flood disasters can have a detrimental impact such as damage to infrastructure, materials, and loss of life. One of the efforts that can be made to carry out early detection of flood disasters is to use a flood prediction system, where this system can monitor water levels, water flow rates, and predict real-time water increases. Information is sent to every citizen using the telegram chatbot. This system is built using several sensors and integrated with Telegram. The sensors used are ultrasonic and water flow sensors. The ultrasonic sensor is used to read the water level in the range of 0-50 cm and the water flow sensor is used to calculate the flow of water entering the test container with an interval of 0-10 liters / minute. Data is sent to telegram in realtime using the firebase database through NodeMCU ESP8266 and the WiFi module. The results of reading water level and water discharge data are processed using Sugeno fuzzy logic. The results obtained in this study indicate that the average error reading from the ultrasonic sensor is 2.43% or 97.58%. The water flow sensor shows an average error of 0.206 liters/minute or the percentage of tool accuracy is 87.06 %.