Wang, Z.; Wang, Y.; Liao, M.; Sun, Y.; Wang, S.; Sun, X.; Shi, X.; Kang, Y.; Tian, M.; Bao, T.; Lu, R. FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System. Sensors2024, 24, 4360.
Wang, Z.; Wang, Y.; Liao, M.; Sun, Y.; Wang, S.; Sun, X.; Shi, X.; Kang, Y.; Tian, M.; Bao, T.; Lu, R. FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System. Sensors 2024, 24, 4360.
Wang, Z.; Wang, Y.; Liao, M.; Sun, Y.; Wang, S.; Sun, X.; Shi, X.; Kang, Y.; Tian, M.; Bao, T.; Lu, R. FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System. Sensors2024, 24, 4360.
Wang, Z.; Wang, Y.; Liao, M.; Sun, Y.; Wang, S.; Sun, X.; Shi, X.; Kang, Y.; Tian, M.; Bao, T.; Lu, R. FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System. Sensors 2024, 24, 4360.
Abstract
Accurate and prompt determination of fire types is essential for effective firefighting and reducing damages. However, traditional methods such as smoke detection, visual analysis, and wireless signals pose unavailability in identifying fire types. This paper introduces FireSonic, an acoustic sensing system that leverages commercial speakers and microphones to actively probe the fire using acoustic signals, effectively identifying indoor fire types. By incorporating beamforming technology, FireSonic first enhances signal clarity and reliability, thus mitigating signal attenuation and distortion. To establish a reliable correlation between fire types and sound propagation, FireSonic quantifies the Heat Release Rate (HRR) of flames by analyzing the relationship between fire heated areas and sound wave propagation delays. Furthermore, the system extracts spatiotemporal features related to fire from channel measurements. Experimental results demonstrate that FireSonic attains an average fire type classification accuracy of 95.5% and a detection latency of less than 400 ms, satisfying the requirements for real-time monitoring. This system significantly enhances the formulation of targeted firefighting strategies, boosting fire response effectiveness and public safety.
Keywords
Acoustic sensing; channel measurements; fire type classification; beamforming
Subject
Computer Science and Mathematics, Signal Processing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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