Flash Flood Monitoring and Forecasting System

Abstract

Traditional flood forecasting methods often fail to predict these events due to their rapid onset and localized nature. To address this challenge, the development of an advanced Flash Flood Monitoring and Forecasting System is essential. A cost-effective, low-powered flood monitoring and forecasting system based on IoT is considered. Here, the system consists of a water level sensor (HC-SR04), rainfall sensor, soil moisture sensor, water flow sensor, and temperature and humidity sensor (DHT 11). A solar power source is used as the main power source for the functioning of sensors. The power bank is used as the secondary power source in this setup. By integrating ESP-NOW with the Blynk app, real-time flood monitoring data from remote sensors can be wirelessly transmitted and displayed on a user-friendly mobile dashboard. The setup ensures low-power communication for sensors while providing instant updates and alerts through the app.