IoT-Based Flood Level Monitoring System with Real-Time Alert and Dashboard Visualization

Authors

  • Naikwade Sairaj Shamrao Undergraduate Student, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India
  • Nannaware Yash Sanjay Undergraduate Student, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India
  • Narkhede Atharva Anantkumar Undergraduate Student, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India
  • Navale Pratap Satish Undergraduate Student, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India
  • Nikampatil Animesh Sushil Undergraduate Student, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India
  • T. Bhaskar Associate Professor, Department of Computer Engineering, Sanjivani College of Engineering, Kopargaon, Affiliated to- SPPU, Pune, Maharashtra, India

Keywords:

Cloud Messaging, Environmental sensor, Flood monitoring, Real-time alert, Smart disaster management

Abstract

In this project, an “IoT-Based Flood Monitoring and Prediction System” is proposed to help communities detect and prepare for potential flood events in advance. The system integrates IoT- enabled sensor technology with weather forecasting APIs and predictive algorithms to monitor and anticipate flood risks effectively. Real-time environmental data such as water level, overflow detection, rainfall forecast, humidity, and temperature is collected using ESP32-based hardware integrated with ultrasonic, float, water flow, and DHT11 sensors. The data is displayed locally on an LCD and transmitted to a Firebase Realtime Database, enabling cloud-based access and analysis.

To enhance its predictive capabilities, the system uses a weighted flood probability algorithm that processes both sensor data and external precipitation forecasts from the OpenWeatherMap API. A ReactJS-based web dashboard provides a user-friendly interface for visualizing live sensor readings, reviewing historical trends, and receiving alerts via Firebase Cloud Messaging. The system also classifies flood risk levels based on computed probabilities, allowing for early warnings and better disaster response.

The hardware implementation was successfully tested in controlled conditions, where both detection and prediction modules performed reliably. By combining real-time monitoring with intelligent forecasting, this system serves as a low-cost, scalable, and impactful solution for smart flood preparedness in both urban and rural regions.

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Published

2025-08-20

Issue

Vol. 2 No. 2 (2025): May – August

Section

Articles