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FireSonic: Design and Implementation of an Ultrasound Sensing-Based Fire Type Identification System.
Wang, Zheng; Wang, Yanwen; Liao, Mingyuan; Sun, Yi; Wang, Shuke; Sun, Xiaoqi; Shi, Xiaokang; Kang, Yisen; Tian, Mi; Bao, Tong; Lu, Ruiqi.
Afiliação
  • Wang Z; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Wang Y; China Electric Power Research Institute, Beijing 100192, China.
  • Liao M; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Sun Y; State Grid Hunan Electric Power Company Limited, Changsha 410004, China.
  • Wang S; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Sun X; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Shi X; China Electric Power Research Institute, Beijing 100192, China.
  • Kang Y; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Tian M; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
  • Bao T; School of Computer Science and Engineering, Central South University, Changsha 410017, China.
  • Lu R; College of Electrical and Information Engineering, Hunan University, Changsha 410012, China.
Sensors (Basel) ; 24(13)2024 Jul 05.
Article em En | MEDLINE | ID: mdl-39001138
ABSTRACT
Accurate and prompt determination of fire types is essential for effective firefighting and reducing damage. However, traditional methods such as smoke detection, visual analysis, and wireless signals are not able to identify 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 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 type 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. The 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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article