Development of real-time flood warning system by integrating IoT and NODEMCU for river monitoring

Ibrahim, Muhammad Haziq (2024) Development of real-time flood warning system by integrating IoT and NODEMCU for river monitoring. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Floods have become a typical yearly occurrence due to the rising frequency of natural catastrophes caused by global warming, particularly during severe rainy seasons when rivers overflow with precipitation that occurs. Since rain cannot be avoided, the creation of a dependable technology capable of predicting flood incidents becomes important. Therefore, this project aims to create a real-time flood warning system for rivers using IoT and NodeMCU. The goal is to provide accurate and timely flood warnings by collecting and transmitting environmental data like water levels and rainfall to a centralized system for processing and analysis. Configuring the hardware components, such as sensors for water level, temperature, ultrasonic, DHT11, and raindrop, as well as constructing a stable power source utilizing a charger module and solar panel, is part of the technique. The program is set up to initialize the sensors, read data, connect to Wi-Fi, and communicate with the web application. Calibration and testing are carried out to guarantee sensor accuracy, confirm decision logic, and validate real-time flood alerts via a web browser. In addition, the research investigates the incorporation of a camera module for visual data collecting. The current results demonstrate effective sensor integration with the ESP8266 Wi-Fi module, laying the groundwork for remote environmental monitoring and automation. Finally, The successful integration of IoT and NodeMCU in the development and deployment of a real-time flood warning system demonstrates the technology's significant potential for improving flood monitoring and emergency response capabilities, including accurate sensor readings, seamless data transfer to MSSQL, and efficient connectivity with web applications to enable timely notifications and valuable flood management insights.

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