Implementation of Fuzzy Logic Sugeno on a Website-Based for Flood Monitoring and Early Detection System

Abstract

Floods are common in Indonesia, especially in Aceh, and are caused by various factors, such as high rainfall during the rainy season, resulting in material and life losses. Developing a flood monitoring and early detection system is essential to reduce the negative impact of flooding. This research introduces the implementation of the Fuzzy Logic Sugeno method on a web-based flood monitoring and early detection system, which uses ESP32 and accurate sensors to monitor water level and water flow. Testing is done through two approaches. First, the water level and flow parameters were manipulated manually to test the system's response to changing conditions. Secondly, tests were conducted automatically until the prototype aquarium was complete to see the system's ability to detect potential flooding. The test results show that the system can automatically recognize potential flooding, take preventive actions, such as opening or closing floodgates, and provide real-time condition information through a Website.

Keywords

• flood
• monitoring system
• esp32
• fuzzy logic sugeno
• real-time website