Fiber-Optic Auditory Nerve of Ground in the Suburb: For Traffic Flow Monitoring

doi:10.1109/ACCESS.2019.2952999

CASIA OpenIR > 模式识别实验室

	Fiber-Optic Auditory Nerve of Ground in the Suburb: For Traffic Flow Monitoring
	Liang, Sheng 1; Zhao, Xiaoting 1; Liu, Ruijun 2; Zhang, Xiaodong 3; Wang, Liang 3; Zhang, Xinghua 1; Lv, Yisheng4 ; Meng, Fanchao 1
发表期刊	IEEE ACCESS
ISSN	2169-3536
	2019
卷号	7 页码:166704-166710
通讯作者	Liu, Ruijun(liuruijun@btbu.edu.cn) ; Zhang, Xiaodong(zhangxd@bgy.cn)
摘要	We propose a novel fiber-optic auditory nerve of ground (FANG) in the suburb based on the fiber-optic distributed vibration sensor (DVS). The feasibility and effectiveness of the principle prototype FANG for traffic flow monitoring are proved and investigated by the field experiment. One of the 31.8 km-long redundant optical fiber of the buried optical-fiber cable for data transmission is utilized as the sensing fiber. Then, the phase-sensitive optical time-domain reflectometer (phi-OTDR) based DVS is realized and regarded as the FANG. The vibration events at 9 observation points with different ground conditions along the sensing fiber are detected by a threshold algorithm during 6.5 hours from 8:00 am. Then, the vibration events are analyzed in combination with the ground conditions to recognize the machine working in the factory, rammer working and the vehicles passed through near different areas and roads. The traffic flow is estimated by the vibration-counting with a counting error that is believed to be in an acceptable range. The distribution and the fluctuation trends of the estimated traffic flow are useful and enlightening for the traffic monitoring and pre-warning of special events, such as an accident. The accuracy can be improved by artificial intelligence methods in the future. It seems that our proposed FANG can be a potential and effective tool for the internet of things, smart ground and smart traffic in the suburb where the video and other information collection methods are not available.
关键词	Fiber-optic distributed vibration sensor (DVS) fiber-optic nerve of ground phi-OTDR smart ground Internet of Things (IoT) smart traffic traffic flow
DOI	10.1109/ACCESS.2019.2952999
关键词[WOS]	PHASE-SENSITIVE OTDR ; PHI-OTDR ; SMART CITIES ; PREDICTION ; SUPPRESSION ; IMPACT ; LASER ; IOT
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61675019] ; Fundamental Research Funds for the Central Universities[2018JBM070] ; Beijing Natural Science Foundation[4192047] ; Beijing Natural Science Foundation[4192047] ; Fundamental Research Funds for the Central Universities[2018JBM070] ; National Natural Science Foundation of China[61675019]
项目资助者	Beijing Natural Science Foundation ; Fundamental Research Funds for the Central Universities ; National Natural Science Foundation of China
WOS研究方向	Computer Science ; Engineering ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号	WOS:000509585900042
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/28601
专题	模式识别实验室
通讯作者	Liu, Ruijun; Zhang, Xiaodong
作者单位	1.Beijing Jiaotong Univ, Sch Sci, Dept Phys, Natl Phys Expt Teaching Demonstrat Ctr,Key Lab Ed, Beijing 100044, Peoples R China 2.Beijing Technol & Business Univ, Sch Comp & Informat Engn, Beijing 100048, Peoples R China 3.Beijing Municipal Inst City Planning & Design BIC, Beijing 100045, Peoples R China 4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liang, Sheng,Zhao, Xiaoting,Liu, Ruijun,et al. Fiber-Optic Auditory Nerve of Ground in the Suburb: For Traffic Flow Monitoring[J]. IEEE ACCESS,2019,7:166704-166710.
APA	Liang, Sheng.,Zhao, Xiaoting.,Liu, Ruijun.,Zhang, Xiaodong.,Wang, Liang.,...&Meng, Fanchao.(2019).Fiber-Optic Auditory Nerve of Ground in the Suburb: For Traffic Flow Monitoring.IEEE ACCESS,7,166704-166710.
MLA	Liang, Sheng,et al."Fiber-Optic Auditory Nerve of Ground in the Suburb: For Traffic Flow Monitoring".IEEE ACCESS 7(2019):166704-166710.