IOT Flood Monitoring Alerting System Using Raspberry pi

  • Unique Paper ID: 195215
  • PageNo: 6775-6782
  • Abstract:
  • The prototype of the IoT Flood Monitoring & Alerting System is developed using a Raspberry Pi as the main processing and control unit. The ultrasonic sensor is mounted near water bodies to continuously measure water level variations, while the raindrop sensor detects rainfall presence and intensity. Environmental parameters such as temperature and humidity are captured using the DHT11 sensor, and atmospheric pressure variations are monitored through the BMP180 sensor to support flood prediction analysis. A MEMS sensor is incorporated to identify abnormal vibrations or sudden changes in water flow, indicating potential flood conditions. All sensors are interfaced with the Raspberry Pi using appropriate GPIO connections and 30-pin connectors. Python programming is used for sensor data acquisition, threshold-based decision making, and communication control. The collected data is displayed on an LCD for local monitoring and uploaded to the ThingSpeak cloud platform for real-time remote visualization. When sensor values exceed predefined safe limits, the system automatically triggers a buzzer and sends alert messages via the GSM module to registered mobile numbers. The entire prototype is powered using a 12V adapter with a regulated power supply to ensure stable and continuous operation, demonstrating an effective and scalable flood monitoring and alerting solution.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article 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.

BibTeX

@article{195215,
        author = {BUDIDINNE RAJU and CHAKALI MULINTI SOMANATH and KOWTHALAM BHARATH and KURUVA GIDDAIAH and GOLLA CHINNA RANGASWAMY and P RAMA THULASI},
        title = {IOT Flood Monitoring Alerting System Using Raspberry pi},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6775-6782},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=195215},
        abstract = {The prototype of the IoT Flood Monitoring & Alerting System is developed using a Raspberry Pi as the main processing and control unit. The ultrasonic sensor is mounted near water bodies to continuously measure water level variations, while the raindrop sensor detects rainfall presence and intensity. Environmental parameters such as temperature and humidity are captured using the DHT11 sensor, and atmospheric pressure variations are monitored through the BMP180 sensor to support flood prediction analysis. A MEMS sensor is incorporated to identify abnormal vibrations or sudden changes in water flow, indicating potential flood conditions. All sensors are interfaced with the Raspberry Pi using appropriate GPIO connections and 30-pin connectors. Python programming is used for sensor data acquisition, threshold-based decision making, and communication control. The collected data is displayed on an LCD for local monitoring and uploaded to the ThingSpeak cloud platform for real-time remote visualization. When sensor values exceed predefined safe limits, the system automatically triggers a buzzer and sends alert messages via the GSM module to registered mobile numbers. The entire prototype is powered using a 12V adapter with a regulated power supply to ensure stable and continuous operation, demonstrating an effective and scalable flood monitoring and alerting solution.},
        keywords = {Flood Monitoring, IoT, Raspberry Pi, Sensor Networks, Early Warning System},
        month = {March},
        }

Cite This Article

RAJU, B., & SOMANATH, C. M., & BHARATH, K., & GIDDAIAH, K., & RANGASWAMY, G. C., & THULASI, P. R. (2026). IOT Flood Monitoring Alerting System Using Raspberry pi. International Journal of Innovative Research in Technology (IJIRT), 12(10), 6775–6782.

Related Articles