Issue |
E3S Web Conf.
Volume 426, 2023
The 5th International Conference of Biospheric Harmony Advanced Research (ICOBAR 2023)
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Article Number | 01008 | |
Number of page(s) | 6 | |
Section | Integrated Sustainable Science and Technology Innovation | |
DOI | https://doi.org/10.1051/e3sconf/202342601008 | |
Published online | 15 September 2023 |
Karangetang Mount Early Warning System using Inference Fuzzy Logic
1 Computer Science Department, BINUS Online Learning, 11480 Bina Nusantara University, Jakarta, Indonesia
2 Informatics Engineering, Faculty of Engineering, 95000 Universitas Katolik De La Salle, Manado, Indonesia
* Corresponding author: immanuela.puspasari@binus.ac.id
Mount Karangetang, located on Siau Island, SITARO Archipelago Regency, is one of Indonesia’s 127 active volcanoes, making it the nation most susceptible to volcanic eruptions. In 2015, an eruption resulted in the displacement of as many as 465 residents, the destruction of four homes, and the loss of gardens, animals, and property. In February of 2023, Mount Karangetang’s volcanic activity increased once more. This project seeks to aid the local Regional Disaster Management Agency in implementing preventative measures or evacuating residents; an early warning system for Mount Karangetang’s eruption will be created. Temperature and seismicity information will be collected through sensors deployed throughout the facility. In the meantime, the distance data is measured based on the real size of the residential location, and the height of the heated clouds is received from the observation post. The current study focuses on the development of a fuzzy logic model with four input variables and a single output variable with three levels: alert, alert, and alert. Depending on the status of the alert, the system can also emit repeated sirens for a specified length. In this study, 81 rules are utilized to determine the status of a warning.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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