Design and Development of an Earthquake Early Warning System Based on IoT Using the Fuzzy Tsukamoto Method

Abstract

The development of an Internet of Things (IoT)-based earthquake early warning system using the Tsukamoto fuzzy method in this study aims to reduce the risk of injuries or fatalities in tall buildings due to earthquakes. This early warning system uses an MPU6050 gyroscope sensor to measure building tilt during an earthquake. The data obtained from the sensor is then processed using an ESP8266 microcontroller. The Tsukamoto fuzzy algorithm is used to classify earthquake risk status into three categories: "Safe," "Alert," and "Danger." Warning notifications are sent in real-time to an application designed using Kodular. The main contribution of this research is the real-time application of the Tsukamoto Fuzzy method in an IoT-based early warning system, utilizing a gyroscope sensor to efficiently measure building tilt and rapidly send warnings. Test results show that the sensor can detect tilt well, in accordance with the predetermined tilt rules, and is able to send warning notifications to the application within 1-2 seconds across all nine test scenarios. However, this system has several limitations, such as the need for further research on a larger scale and in more varied environments. This system provides a solution for disaster relief efforts for earthquake victims in tall buildings and can be further developed in the future.

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Issue

Vol. 11 No. 2 (2026): JUSTINDO

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Copyright (c) 2026 Muhammad Zulfikar Adipradana, Ari Eko Wardoyo, Taufiq Timur Warisaji

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