Early Flood Warning System in Samarinda City

Authors

  • Gusvi Ainur Ikhsan Isnor Politeknik Negeri Samarinda
  • Abdullah Hanif Politeknik Negeri Samarinda
  • Irwansyah Politeknik Negeri Samarinda

DOI:

https://doi.org/10.59934/jaiea.v6i1.2709

Keywords:

Android, ESP32, Firebase, Flood, Fuzzy Logic, HTML, Raindrop, Ultrasonic

Abstract

This study aims to design and implement an Early Flood Warning System in Samarinda City to help the community monitor potential flooding in real-time. The system uses an ESP32 microcontroller connected to the Firebase Realtime Database and is equipped with two main sensors: a raindrop sensor to detect rainfall intensity and an ultrasonic sensor to measure water surface height. The sensor data are displayed on an LCD 16x2 and sent directly to Firebase, which can then be accessed via an Android application or a local web interface based on HTML. The system also includes a buzzer that serves as an alarm when the detected condition reaches a danger level. In addition, a fuzzy logic method is applied to determine the flood risk level based on the combination of rainfall intensity and water surface distance. Based on the test results, the system operates stably with a high level of 80% accuracy in displaying data and delivering timely warning notifications. Therefore, this system can serve as an effective and practical flood mitigation tool for communities in the Samarinda area.

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References

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Published

2026-10-15

How to Cite

Ainur Ikhsan Isnor, G., Hanif, A., & Irwansyah. (2026). Early Flood Warning System in Samarinda City. Journal of Artificial Intelligence and Engineering Applications (JAIEA), 6(1), 382–388. https://doi.org/10.59934/jaiea.v6i1.2709