IoT Based Early Flood Alerting System


Authors : Hakesh Nadella; Jyothir Ashish; Dr. R.Brindha

Volume/Issue : Volume 9 - 2024, Issue 4 - April

Google Scholar : https://tinyurl.com/3v2taynw

Scribd : https://tinyurl.com/bdcnxu56

DOI : https://doi.org/10.38124/ijisrt/IJISRT24APR2438

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Abstract : The frequency and intensity of floods have increased recently in many parts of the world, increasing the need for cutting-edge technology solutions to mitigate the effects of these natural disasters. It is crucial to keep aneye on the water flow and get early emergency alerts regarding the water level based on the riverbed in order toprevent such disasters. The goal of this project is to create asystem that employs cutting-edge sensors and a Wi-Fi module to detect the water level. The suggested system has a number of sensors that can track important variables, including temperature, humidity, and water level. If the level crosses a certain threshold, The system will send out early warnings to everyone, alerting them to the likelihood of floods. To process and store data, we have linked the Arduino UNO to each sensor. The system can notify a wider audience by sending email alerts, ensuring that individuals in flood-prone areas receive timely warnings. Additionally, the use ofa Wi-Fi module enables real-time data transmission and remote monitoring of water levels, allowing authorities to take preemptive measures and minimize the impact of potential floods. By integrating advanced sensors with communication technology, this project aims to enhance early warning systems and contribute to more effective disaster management strategies in vulnerable regions. Ultimately, the implementation of such innovative solutions can significantly improve community resilience and reduce the adverse consequences of flooding events.

Keywords : IoT (Internet of Things), Arduino UNO, Social Media Integration, GSM (Global System for Mobile Communications) Technology, Blynk Application.

References :

  1. Abdullahi, Salami Ifedapo, Mohamed Hadi Habaebi, and Noreha Abd Malik. "Intelligent flood disaster warning on the fly: developing IoT-based management platform and using 2- class neural network to predict flood status." Bulletin of Electrical Engineering and Informatics 8, no. 2 (2019): 706- 717.
  2. Hashi, Abdirahman Osman, Abdullahi Ahmed Abdirahman, Mohamed Abdirahman Elmi, Siti Zaiton Mohd Hashi, and Octavio Ernesto Romo Rodriguez. "A real-time flood detection system based on machine learning algorithms with emphasis on deep learning." International Journal of Engineering Trends and Technology 69, no. 5 (2021): 249-256.
  3. Ancona, Massimo, Andrea Dellacasa, Giorgio Delzanno, A. L. Camera, and Ivano Rellini. "An “Internet of Things” vision of the flood monitoring problem." In The Fifth International Conference on Ambient Computing, Applications, Services and Technologies, vol. 3, pp. 26-29. 2015.
  4. Manohar, N., and A. U. Archana. "Cloud-based flood prediction using iot devices and machine learning algorithms." In 2021 Second International Conference on Electronics and Sustainable Communication Systems (ICESC), pp. 754-762. IEEE, 2021.
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  15. Khan, Amina, Sachin Kumar Gupta, Elyas Ibraheem Assiri, Mamoon Rashid, Younus Talha Mohammed, Mohd Najim, and Yousef Ruzayq Alharbi. "Flood monitoring and warning system: Het-Sens a proposed model." In 2020 2nd international conference on computer and information sciences (ICCIS), pp.

The frequency and intensity of floods have increased recently in many parts of the world, increasing the need for cutting-edge technology solutions to mitigate the effects of these natural disasters. It is crucial to keep aneye on the water flow and get early emergency alerts regarding the water level based on the riverbed in order toprevent such disasters. The goal of this project is to create asystem that employs cutting-edge sensors and a Wi-Fi module to detect the water level. The suggested system has a number of sensors that can track important variables, including temperature, humidity, and water level. If the level crosses a certain threshold, The system will send out early warnings to everyone, alerting them to the likelihood of floods. To process and store data, we have linked the Arduino UNO to each sensor. The system can notify a wider audience by sending email alerts, ensuring that individuals in flood-prone areas receive timely warnings. Additionally, the use ofa Wi-Fi module enables real-time data transmission and remote monitoring of water levels, allowing authorities to take preemptive measures and minimize the impact of potential floods. By integrating advanced sensors with communication technology, this project aims to enhance early warning systems and contribute to more effective disaster management strategies in vulnerable regions. Ultimately, the implementation of such innovative solutions can significantly improve community resilience and reduce the adverse consequences of flooding events.

Keywords : IoT (Internet of Things), Arduino UNO, Social Media Integration, GSM (Global System for Mobile Communications) Technology, Blynk Application.

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