Development Of An Iot And Fuzzy Logic Based Early Warning System Prototype For Toxic Gas Monitoring In Kawah Timbang, Dieng

Authors

  • Kunti Najma Jalia Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an, Indonesia
  • Muhammad Assegaf Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an, Indonesia
  • Sihabuddin Rifqi Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an, Indonesia
  • Miftahul Fuadi Mechanical Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an,
  • Fi Amalia Utami Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an, Indonesia
  • Nahar Mardiyantoro Informatics Engineering, Faculty of Engineering and Computer Science, Universitas Sains Al-Qur’an, Indonesia

DOI:

https://doi.org/10.32699/cathasaintifica.v4i1.10334

Keywords:

Internet of Things, Fuzzy Logic, Early Warning System, Toxic Gas, Volcanic Disaster Mitigation

Abstract

Volcanic gas emissions in the Dieng Plateau pose serious hazards, particularly at Kawah Timbang, where high concentrations of carbon dioxide (CO₂), hydrogen sulfide (H₂S), and sulfur dioxide (SO₂) threaten surrounding communities. Recorded CO₂ levels have reached 10.000 ppm, far exceeding the safe threshold and highlighting the urgency of an automatic early warning system that can deliver real-time alerts to minimize evacuation delays and potential fatalities. This study aims to design and evaluate an early warning system prototype based on the Internet of Things (IoT) and fuzzy logic for CO₂ monitoring at Kawah Timbang.  The prototype uses an ESP32 microcontroller, MQ-135 sensor, DHT20 sensor, OLED display, buzzer, and IoT applications (Blynk and Telegram) to provide both local and remote alerts.  Results show that the prototype effectively detects CO₂ in real time, classifies hazard levels into safe, alert, and hazardous categories, and transmits notifications with a response time of less than 10 seconds. The integration of IoT and fuzzy logic offers a practical and adaptive solution for volcanic disaster mitigation. Further development should include multi-gas detection, field deployment, and the use of machine learning to enhance accuracy and system resilience.

References

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Published

2026-05-31

Issue

Vol. 4 No. 1 (2026): May 2026 Article-in-Press

Section

Article

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Copyright (c) 2026 Kunti Najma Jalia, Muhammad Assegaf, Sihabuddin Rifqi, Miftahul Fuadi, Fi Amalia Utami, Nahar Mardiyantoro

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How to Cite

Development Of An Iot And Fuzzy Logic Based Early Warning System Prototype For Toxic Gas Monitoring In Kawah Timbang, Dieng. (2026). CATHA SAINTIFICA, 4(1), 1-9. https://doi.org/10.32699/cathasaintifica.v4i1.10334

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