摘要
现代科技发展带来高层建筑和复杂建筑结构增多,导致消防员很容易在火场内受到生命危险。针对消防人员进入复杂火场后的生命体征状态及室内定位问题,提出了一套完整的协助系统。提出使用LSTM神经网络预测消防人员的动作姿态,使用光电传感器监测消防员的心率血氧以及周边气体环境。同时,提出了一种基于超宽带通信定位与高精度惯性元件导航进行数据融合的室内消防员定位手段。最后,终端通过LoRa-170M无线系统上传给移动监测平台,利用LabVIEW软件完成了监测上位机,并通过实验验证了其可靠性及稳定程度。
Since the development of modern technology, the number of high buildings and complex structures keeps ascending,which leads to the vital hazard of firefighters. This paper proposes a complete aid system to duel with the issues on vital signal detection and indoor location for the firefighters. In this paper, LSTM Neural Network is employed to classified the attitude and movement of the firefighter, and particular photoelectric sensors are used to detect the heard rate, blood oxygen saturation and the gas surrounded. At the meantime, this paper proposes a indoor location system based on the data fusion of the Ultra-WideBand location and the inertial navigation. Finally data above are transmitted via LoRa-170 M Network to the monitoring platform which is built up with the help of LabVIEW. At the end, experiments are designed to verify the ability and stability of the system.
作者
王圣哲
王博
高鸣远
罗亮
Wang Shengzhe;Wang Bo;Gao Mingyuan;Luo Liang(School of Electro-Optical Engineering,Changchun University of Science and Technology,Changchun 130000,China)
出处
《电子技术应用》
2020年第12期72-77,共6页
Application of Electronic Technique
关键词
消防救援
生命体征监测
室内定位
LSTM神经网络
超宽带技术
firefighting rescue
vital signal detection
indoor location system
LSTM neural network
Ultra-WideBand technology
