Distributed Acoustic Sensing for Crowd Motion and Firecracker Explosions in the Fireworks Show

烟火 声学 环境科学 地质学 计算机科学 运动(物理) 航空航天工程 物理 工程类 人工智能 地理 考古
作者
Jiangnan Lin,Wenbin Jiang,Zhou Yong,Bin Liu,Minghui Zhao,Zhuo Xiao,Lingmin Cao,Min Xu
出处
期刊:Seismological Research Letters [Seismological Society]
卷期号:95 (4): 2195-2207 被引量:1
标识
DOI:10.1785/0220230346
摘要

Abstract Urban seismology has recently emerged as a vibrant scientific field, driven by the growing interest in seismic signals generated by major public events, sports gatherings, and transportation services. However, deploying dense traditional seismometers in economically active, densely populated urban areas with heavy traffic poses significant challenges. In this study, we conducted a field experiment utilizing distributed acoustic sensing (DAS) technology during a fireworks display in Guangzhou on 5 February 2023. About 572 m of optical fiber was turned into 286 seismic sensors and deployed on LingShan Island to monitor various vibration signals generated during the fireworks show. Our analysis revealed substantial correlations between crowd motions during different phases of the event and ambient noise features recorded by DAS. Moreover, the cross-correlation functions of the ambient noise with its dispersion characteristics pointed to near-field pedestrian activity as the primary noise source. Real-time heat maps of human crowd motions were reconstructed from DAS recording, offering significant insights into the variations of activity intensity across different locations. Discerning fireworks events on the DAS array is more effective than on a scattered seismometer array, because it is easier to ensure that the same event is picked for all the sites in the DAS dense linear configuration. The DAS data inspection allowed us to pick up a total of 549 firecracker explosions in comparison to the seismometer data that only allowed us to detect 116 firecracker events. The heights of fireworks were located by the grid-search method and predominantly distributed at 75–300 m, closely aligning with actual fireworks explosion locations. Our findings underscore that the DAS technology can monitor crowd motion and detect vibration signals in the air, bridging the gap between fundamental earth science research and human social activities.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
无奈萝发布了新的文献求助10
刚刚
Zr完成签到,获得积分10
1秒前
火星上的如松完成签到,获得积分10
1秒前
Lee发布了新的文献求助10
5秒前
5秒前
兰胖子发布了新的文献求助10
5秒前
戊丙完成签到,获得积分10
6秒前
6秒前
7秒前
Lucas应助Estrella12138采纳,获得10
7秒前
CipherSage应助科研通管家采纳,获得10
8秒前
CodeCraft应助科研通管家采纳,获得10
8秒前
脑洞疼应助科研通管家采纳,获得30
8秒前
思源应助科研通管家采纳,获得30
8秒前
今后应助科研通管家采纳,获得10
8秒前
笑笑应助科研通管家采纳,获得10
8秒前
CipherSage应助科研通管家采纳,获得10
8秒前
Ava应助科研通管家采纳,获得10
8秒前
大个应助科研通管家采纳,获得10
8秒前
8秒前
小马甲应助科研通管家采纳,获得10
8秒前
Owen应助科研通管家采纳,获得10
8秒前
9秒前
9秒前
9秒前
9秒前
9秒前
直率小霜发布了新的文献求助10
9秒前
脑洞疼应助寻凝采纳,获得10
9秒前
10秒前
方丈渣渣发布了新的文献求助10
10秒前
华仔应助孙成采纳,获得10
11秒前
12秒前
风清扬发布了新的文献求助30
13秒前
14秒前
阿达我的完成签到,获得积分20
14秒前
冷傲疾完成签到,获得积分10
14秒前
16秒前
17秒前
阿达我的发布了新的文献求助10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Social Cognition: Understanding People and Events 800
Signals, Systems, and Signal Processing 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6025410
求助须知:如何正确求助?哪些是违规求助? 7662675
关于积分的说明 16179208
捐赠科研通 5173549
什么是DOI,文献DOI怎么找? 2768262
邀请新用户注册赠送积分活动 1751639
关于科研通互助平台的介绍 1637724