IoT-based cloud monitoring system for building fires

This paper presents an IoT (Internet of Things) based smart building fire cloud monitoring system to enhance fire safety in smart buildings. It integrates low-cost sensors and real-time video surveillance for real-time environmental data collection. Data are uploaded to the cloud for remote monitoring via a custom web interface. The system features an artificial neural network model that reduces computational complexity and response time, achieving >95% accuracy in fire prediction. It assists in planning evacuation routes based on fire location, enhancing safety and efficiency. Laboratory and field tests confirm reliable performance, and the novel system will find applications in smart fire detection and prevention.

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Publication Details

Journal
International Journal of Metrology and Quality Engineering
Published
2025-01-01
DOI
https://doi.org/10.1051/ijmqe/2024020
Citations
1
Primary Topic
Fire Detection and Safety Systems
Type
article
Field-Weighted Citation Impact
1.30
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article

IoT-based cloud monitoring system for building fires

Yazhou Xie, Guangyong Pan, Qingping Yang
1 citations
International Journal of Metrology and Quality Engineering
Fire Detection and Safety Systems
1.30
article

IoT-based cloud monitoring system for building fires

Yazhou Xie, Guangyong Pan, Qingping Yang
article en
1 citations

Abstract

This paper presents an IoT (Internet of Things) based smart building fire cloud monitoring system to enhance fire safety in smart buildings. It integrates low-cost sensors and real-time video surveillance for real-time environmental data collection. Data are uploaded to the cloud for remote monitoring via a custom web interface. The system features an artificial neural network model that reduces computational complexity and response time, achieving >95% accuracy in fire prediction. It assists in planning evacuation routes based on fire location, enhancing safety and efficiency. Laboratory and field tests confirm reliable performance, and the novel system will find applications in smart fire detection and prevention.

International Journal of Metrology and Quality EngineeringVol. 16
North University of China (CN), Brunel University of London (GB)
Openalex Percentile: Top 26%
Fire Detection and Safety Systems
1.30
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