HearFire

Author:

Wang Zheng1ORCID,Wang Yanwen2ORCID,Tian Mi2ORCID,Shen Jiaxing3ORCID

Affiliation:

1. College of Electrical and Information Engineering, Hunan University, Changsha, Hunan, China

2. College of Electrical and Information Engineering, Hunan University, Changsha, China

3. The Department of Computing and Decision Sciences, Lingnan University, Hong Kong, China

Abstract

Indoor conflagration causes a large number of casualties and property losses worldwide every year. Yet existing indoor fire detection systems either suffer from short sensing range (e.g., ≤ 0.5m using a thermometer), susceptible to interferences (e.g., smoke detector) or high computational and deployment overhead (e.g., cameras, Wi-Fi). This paper proposes HearFire, a cost-effective, easy-to-use and timely room-scale fire detection system via acoustic sensing. HearFire consists of a collocated commodity speaker and microphone pair, which remotely senses fire by emitting inaudible sound waves. Unlike existing works that use signal reflection effect to fulfill acoustic sensing tasks, HearFire leverages sound absorption and sound speed variations to sense the fire due to unique physical properties of flame. Through a deep analysis of sound transmission, HearFire effectively achieves room-scale sensing by correlating the relationship between the transmission signal length and sensing distance. The transmission frame is carefully selected to expand sensing range and balance a series of practical factors that impact the system's performance. We further design a simple yet effective approach to remove the environmental interference caused by signal reflection by conducting a deep investigation into channel differences between sound reflection and sound absorption. Specifically, sound reflection results in a much more stable pattern in terms of signal energy than sound absorption, which can be exploited to differentiate the channel measurements caused by fire from other interferences. Extensive experiments demonstrate that HireFire enables a maximum 7m sensing range and achieves timely fire detection in indoor environments with up to 99.2% accuracy under different experiment configurations.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Hardware and Architecture,Human-Computer Interaction

Reference63 articles.

1. Allied Market Research . Fire Alarm and Detection System Market. https://www.alliedmarketresearch.com/fire-alarm-and-detection-system-market-A12493 , 2021 . Allied Market Research. Fire Alarm and Detection System Market. https://www.alliedmarketresearch.com/fire-alarm-and-detection-system-market-A12493, 2021.

2. Recent trends in porous sound-absorbing materials;Arenas Jorge P;Sound & vibration,2010

3. Engineering Noise Control

4. Sensors for fire detection

5. Flow and Temperature Fields in the Fire-Ball of an Inductively Coupled Plasma

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multi-sensor Data Fusion for Early Fire Estimation Using ML Techniques;Lecture Notes in Electrical Engineering;2023-12-16

2. Non-intrusive Anomaly Detection of Industrial Robot Operations by Exploiting Nonlinear Effect;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2022-12-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3