Home Journals Articles Updates About
CN
image
收藏切换
BP neural network-based personnel positioning-tracking-stationary alarm system for emergency rescue
收藏切换
PDF
Li Wang1, Zhe Wang1, Wenling Guan1, Jiaqi Zhang1, Chaolin Liu2, Yuying Meng1, 3
China Safety Science Journal | 2026, 36(4) : 204 - 210
Less
收藏切换
China Safety Science Journal | 2026, 36(4): 204-210
• Public Safety and Emergency Management •
BP neural network-based personnel positioning-tracking-stationary alarm system for emergency rescue
Full
Li Wang1, Zhe Wang1, Wenling Guan1, Jiaqi Zhang1, Chaolin Liu2, Yuying Meng1, 3
Affiliations
  • 1School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China
  • 2Information Research Institute of Ministry of Emergency Management (MEM), Beijing 100029, China
  • 3Shandong Jinweianheng Education Technology Co., Ltd., Ji'nan Shandong 250003, China
Published: 2026-04-28 doi: 10.16265/j.cnki.issn1003-3033.2026.04.0177
Outline
收藏切换

To ensure timely rescue of trapped personnel in fire scenarios, a personnel positioning-tracking-stationary alarm system was proposed by combining BP neural networks and DS-TWR technology. The system was developed based on the LabVIEW platform, where the BP neural network learned the error patterns of multipath effects and non-line-of-sight propagation, corrected DS-TWR ranging errors, and achieved precise personnel positioning and trajectory tracking. By calculating the movement distance within a defined time, the system evaluated personnel motion status and established thresholds of displacement and time to trigger alarms, which automatically activated alerts when a person remained stationary beyond the safety threshold. Test results show that the system achieves centimeter-level static and dynamic positioning accuracy under both normal and metal/electromagnetic interference environments. It features high positioning precision and favorable stability, enables accurate trajectory generation, delivers reliable static personnel alarms, and maintains a low response latency.

emergency rescue  /  back propagation (BP) neural network  /  personnel positioning-tracking-stationary alarm  /  double-sided two-way ranging (DS-TWR)  /  laboratory virtual instrument engineering workbench (LabVIEW)
Li Wang, Zhe Wang, Wenling Guan, Jiaqi Zhang, Chaolin Liu, Yuying Meng. BP neural network-based personnel positioning-tracking-stationary alarm system for emergency rescue[J]. China Safety Science Journal, 2026 , 36 (4) : 204 -210 . DOI: 10.16265/j.cnki.issn1003-3033.2026.04.0177
Appendix
Less
Year 2026 volume 36 Issue 4
PDF
70
7
Cite this Article
BibTeX
Article Info
doi: 10.16265/j.cnki.issn1003-3033.2026.04.0177
  • Receive Date：2025-12-14
  • Online Date：2026-07-08
  • Published：2026-04-28
Article Data
Affiliations
History
  • Received：2025-12-14
  • Revised：2026-02-26
Funding
Affiliations
    1School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China
    2Information Research Institute of Ministry of Emergency Management (MEM), Beijing 100029, China
    3Shandong Jinweianheng Education Technology Co., Ltd., Ji'nan Shandong 250003, China
References
Share
https://castjournals.cast.org.cn/joweb/zgaqkxxb/EN/10.16265/j.cnki.issn1003-3033.2026.04.0177
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House