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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Integrated IoT-Based Fire Prevention and Evacuation System for High-Rise Buildings
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%.
Integrated IoT-Based Fire Prevention and Evacuation System for High-Rise Buildings
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%.
Integrated IoT-Based Fire Prevention and Evacuation System for High-Rise Buildings
Maharmi, Benriwati (Autor:in) / Samsudin, Samsudin (Autor:in) / Ramdha, Triana (Autor:in) / Hanifulkhair, Hanifulkhair (Autor:in)
11.12.2024
doi:10.36842/jomase.v68i3.383
Journal of Ocean, Mechanical and Aerospace -science and engineering-; Vol 68 No 3 (2024): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse); 161-168 ; 2527-6085 ; 2354-7065 ; 10.36842/jomase.v68i3
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
624
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