Integrated IoT-Based Fire Prevention and Evacuation System for High-Rise Buildings

  • Benriwati Maharmi Department of Electrical Engineering, Sekolah Tinggi Teknologi Pekanbaru, Indonesia
  • Samsudin Samsudin Department of Electrical Engineering, Sekolah Tinggi Teknologi Pekanbaru, Indonesia
  • Triana Ramdha Department of Electrical Engineering, Sekolah Tinggi Teknologi Pekanbaru, Indonesia
  • Hanifulkhair Hanifulkhair Department of Electrical Engineering, Sekolah Tinggi Teknologi Pekanbaru, Indonesia

Abstract

Conventional fire protection systems, characterized by low installation costs, often lack the sophistication to provide optimal protection, especially in high-rise buildings. This study aims to refine the operational productivity concerning fire prevention and evacuation by embracing a detailed fire safety framework that leverages Internet of Things (IoT) capabilities. This prototype integrates SMS and phone call alerts to facilitate timely response in case of fire detection. The system utilizes three key sensors: a KY-026 flame sensor module, an MQ-2 gas and gas sensor, and an LM35 temperature sensor. Testing results indicate significant sensor value variations between normal and fire conditions. The KY-026 flame sensor module, for instance, exhibited an average reading of 137.3 under normal conditions and 895.2 during fire detection. Similarly, the MQ-2 sensor recorded 1234.7 ppm and 4237.8 ppm, respectively. The LM35 temperature sensor measured 28.34°C and 48.46°C under normal and high-temperature conditions. Despite the sensors showcasing commendable efficacy, they displayed a minor error margin fluctuating between 0.04% and 1.08%.

Published
Dec 11, 2024
How to Cite
MAHARMI, Benriwati et al. Integrated IoT-Based Fire Prevention and Evacuation System for High-Rise Buildings. Journal of Ocean, Mechanical and Aerospace -science and engineering-, [S.l.], v. 68, n. 3, p. 161-168, dec. 2024. ISSN 2527-6085. Available at: <https://isomase.org/Journals/index.php/jomase/article/view/383>. Date accessed: 09 oct. 2025. doi: http://dx.doi.org/10.36842/jomase.v68i3.383.
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