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All Journal Infact: Jurnal Sains dan Komputer
Muhammad Iqra Nur Fajar
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Computer Science & IT Electrical & Electronics Engineering

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Iot-Based Early Fire Detection System Uses MQ-2 Smoke Sensor And DS18B20 Temperature Sensor Aulyah Zakilah Ifani; Muhammad Iqra Nur Fajar; Athaillah Aufa Badila
Infact: International Journal of Computers Vol. 10 No. 01 (2026): Journal of Science and Computers
Publisher : Universitas Kristen Immanuel

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61179/infact.v10i01.763

Abstract

Fire disasters remain a major threat in Indonesia, especially in dense housing, offices, and industrial zones. Delayed detection leads to heavy property losses and fatalities, since blazes are often noticed only after flames grow and smoke spreads. This study introduces an IoT early warning system combining an MQ-2 smoke sensor and a DS18B20 temperature sensor on a NodeMCU ESP8266. Using the ADDIE model—analysis, design, development, implementation, evaluation—the prototype was built and tested in laboratory simulations. Tests show the MQ-2 detects smoke at ?400 ppm, while the DS18B20 measures temperatures ?60 °C with ±0.5 °C precision. The dual-sensor setup delivers over 95 % accuracy, alerts within two minutes, and keeps false alarms below 5 %, providing an effective and economical tool for urban fire mitigation. Its low-cost components and Wi-Fi connectivity enable real-time alerts to smartphones or control rooms, facilitating response and scalable deployment in communities.
Co-Authors Athaillah Aufa Badila Aulyah Zakilah Ifani