HearFire: Indoor Fire Detection via Inaudible Acoustic Sensing
Zheng Wang, Yanwen Wang, Mi Tian, Jiaxing Shen
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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers2
- Talk2Radar: Talking to mmWave Radars via Smartphone SpeakerKaiyan Cui, Leming Shen, Yuanqing Zheng, Fu Xiao et al.INFOCOM 2024 · 8 citations
- Push the Limit of Acoustic Indoor Fire MonitoringZheng Wang, Xiaoqi Sun, Yuanqing Zheng, Yanwen WangINFOCOM 2025
Builds on5
- Push the Limit of Acoustic Gesture RecognitionYanwen Wang, Jiaxing Shen, Yuanqing ZhengINFOCOM 2020 · 80 citations
- LASense: Pushing the Limits of Fine-grained Activity Sensing Using Acoustic SignalsDong Li, Jialin Liu, Sunghoon Ivan Lee, Jie XiongUbiComp 2022 · 36 citations
- AMT: Acoustic Multi-target Tracking with Smartphone MIMO SystemChao Liu, Penghao Wang, Ruobing Jiang, Yanmin ZhuINFOCOM 2021 · 26 citations
- Push the Limit of Device-Free Acoustic Sensing on Commercial Mobile DevicesHaiming Cheng, Wei LouINFOCOM 2021 · 23 citations
- Model-based Head Orientation Estimation for Smart DevicesQiang Yang, Yuanqing ZhengUbiComp 2021 · 18 citations
Related papers
- LoEar: Push the Range Limit of Acoustic Sensing for Vital Sign MonitoringLei Wang, Wei Li, Ke Sun, Fusang Zhang et al.UbiComp 2022 · 34 citations
- EarHover: Mid-Air Gesture Recognition for Hearables Using Sound Leakage SignalsShunta Suzuki, Takashi Amesaka, Hiroki Watanabe, Buntarou Shizuki et al.UIST 2024 · 5 citations
- BlinkListener: "Listen" to Your Eye Blink Using Your SmartphoneJialin Liu, Dong Li, Lei Wang, Jie XiongUbiComp 2021 · 41 citations
- Embracing Distributed Acoustic Sensing in Car Cabin for Children Presence DetectionYuqi Su, Fusang Zhang, Kai Niu, Tianben Wang et al.UbiComp 2024 · 26 citations
- VECTOR: Velocity Based Temperature-field Monitoring with Distributed Acoustic DevicesHaoran Wan, Lei Wang, Ting Zhao, Ke Sun et al.UbiComp 2022 · 22 citations
