Flood Detection and Monitoring using IOT

Abstract

One of the most destroying characteristic pf natures that can happen any place in the globe is flooding. In consideration to keep an eye on the surge circumstance particularly in a low line range, a framework was put and developed to track the Dam water level, Door opening status and precipitation level in real-time. A application-based data source for the open, reacting to their require for data on water conditions and flooding, and a Status page for data approximately flooding between the included specialists and specialists to move forward their obligations and participation are the two essential objectives of the made framework. A sensor organizes, a processing/transmission unit, and a database/application server make up the made framework. With the offer assistance of a remote sensor arrange that communicates with the application server over versatile Common Parcel Radio Benefit (GPRS), it is conceivable to remotely screen this real-time information of water condition. To encourage communication between the application server a microcontroller will be utilized. Ultrasonic sensors will be utilized to bring the correct level of the water in the dam. The entryway opening status will be picked up through a few sensors like water sensors and rain sensors. The versatile application which is made and associated with a few IOT Sensors will be having two major segments i.e. Flood Status and Emergency services. A few crisis administrations like healing centers, transport will be included in this application which will be valuable in the overwhelmed circumstances and post overflowed circumstances.

Introduction

Floods are among the most destructive and frequent natural disasters, with increasing severity due to climate change. Traditional flood detection systems are limited by delayed alerts, lack of real-time data, and accessibility issues, especially in rural and developing areas. To address these challenges, the text proposes an IoT-based Early Flood Detection and Alert System, which leverages sensors, wireless communication, and cloud integration to monitor environmental variables and issue real-time warnings.

Key Points:

Problem Overview:

• Natural disasters like floods are unavoidable and cause widespread destruction.

• Existing flood monitoring systems are outdated, slow, and inaccessible to many people.

• In India and countries like Sri Lanka, floods are worsened by climate change and slow government response times.

Proposed Solution: IoT-Based Flood Monitoring System:

• Uses ultrasonic sensors, rain sensors, and water level detectors connected to a NodeMCU ESP8266 microcontroller.

• Data is transmitted via Wi-Fi to a cloud platform, where it's processed and monitored.

• When water levels exceed set thresholds, the system sends real-time alerts to users via a mobile/web app.

• Aims to improve response time, reduce property damage, and save lives.

Technical Implementation:

Hardware Components:

• ESP8266-12E: Wi-Fi chip for wireless data transfer.

• Ultrasonic sensor: Measures water level by detecting distance.

• Voltage regulator, USB converter, flash/reset buttons: Ensure system power stability and allow programming.

System Architecture:

• Sensors collect environmental data.

• NodeMCU transmits data to the cloud.

• Cloud platform analyzes data and triggers alerts.

• Users are notified via a mobile app, enabling early evacuation or safety measures.

Test Results:

• Accurate water level detection.

• Reliable Wi-Fi connectivity.

• Successful alert notifications.

• Functional user interface for monitoring.

Literature Survey Insights:

• Various global studies support the integration of IoT, AI, and cloud computing for flood monitoring.

• Highlighted challenges include reliance on internet connectivity and the need for systems that work in low-resource settings.

• Commercial systems exist but often aren't accessible or scalable for rural use.

Future Scope:

• Incorporate AI and machine learning for predictive analytics.

• Add more sensors (e.g., soil moisture, rain gauges) for comprehensive monitoring.

• Use solar power for sustainability.

• Implement mobile mesh networks or satellite communications for remote areas.

• Integrate with government disaster response systems for large-scale alerts.

Conclusion

The proposed Internet of Things (IoT) flood disaster management system aims to implement innovative strategies to reduce the risk of human casualties and damage to critical infrastructure from both natural and man-made disasters. This initiative outlines a plan to deploy affordable wireless sensor networks capable of detecting various disasters, including floods, wildfires, and landslides, and subsequently alerting residents along coastal areas. Ultimately, this study seeks to establish a foundation for IoT disaster management systems, highlighting insights from prior research and identifying future research directions to address challenges in disaster management effectively. IoT-based flood monitoring and detection systems present a powerful, forward-looking solution for minimizing the risks and damages caused by floods. By harnessing interconnected devices, real-time data collection, and predictive analytics, these systems provide a seamless, automated approach to flood management. They enable early detection, immediate alerts, and actionable insights, allowing for proactive responses and reducing the vulnerability of both urban and rural communities. As IoT technology continues to evolve, it will enhance the resilience of cities and regions, offering a scalable and accessible tool for disaster mitigation. Ultimately, the integration of IoT into flood detection marks a critical step towards creating smart, adaptive, and safer environments in the face of climate-induced challenges.

References

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Copyright

Copyright © 2025 Sanket Patil, Anushka Salve, Pratik Wagh, Vaishnavi Wakchaure. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.