现代电子技术2025，Vol.48Issue(7)：155-162,8.DOI:10.16652/j.issn.1004-373x.2025.07.022
基于边缘计算的在途危险品姿态识别方法
Edge computing based attitude recognition of dangerous goods in transit
张伟 1邓士杰 1于贵波1
作者信息
- 1. 陆军工程大学石家庄校区,河北 石家庄 050003
- 折叠
摘要
Abstract
Aiming at the monitoring of the safety status of the in-transit dangerous goods,for example,chemicals and pyrotechnic products,an in-transit dangerous goods attitude recognition method based on edge calculating is proposed to recognize the behavioral attitude of these goods in real time.In the method,the edge computing devices are adopted as the data processing platform.Firstly,the three-axis motion data of dangerous goods in the process of transportation is captured by the attitude sensor in real time;then,the sliding window technology and feature extraction are integrated to complete the processing of the data flow,and the behavioral attitude sample data of dangerous goods in transit are obtained;finally,the classification model based on the deep learning CNN-BiLSTM-Attention is used to complete the recognition of behavioral attitude of dangerous goods.The experimental results show that the method can accurately and reliably recognize the behavioral postures of in-transit dangerous goods thanks to the joint advantages of edge computing and deep learning,so it has a certain practical application value.关键词
边缘计算/在途危险品/姿态传感器/滑动窗口技术/特征提取/深度学习Key words
edge computing/in-transit dangerous goods/attitude sensor/sliding window technique/feature extraction/deep learning分类
信息技术与安全科学引用本文复制引用
张伟,邓士杰,于贵波..基于边缘计算的在途危险品姿态识别方法[J].现代电子技术,2025,48(7):155-162,8.
