Beyond 5G for digital twins of UAVs

Lv, Zhihan; Chen, Dongliang; Feng, Hailing; Lou, Ranran

doi:10.1016/j.comnet.2021.108366

Cited by 22 publications

(10 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the rapid development of 5G, Internet of ings, and computer technology, all walks of life are now using these new technologies and gradually replacing labor, freeing people from heavy and trivial daily work. Education has been around since ancient times [31][32][33]. 4G networks are built for mobile phones, not optimized for the Internet of ings.…”

Section: Embedded Operating Logic Of the Computer Hardwarementioning

confidence: 99%

Design and Research of Computer-Aided Translation Teaching Course under the Background of Embedded Microprocessor Wireless Communication

Yuan

Zhu

2022

Scientific Programming

View full text Add to dashboard Cite

The background of wireless communication is the background of the current society. On this basis, the use of embedded microprocessors for computer-assisted translation teaching courses can well cultivate the practical abilities of college students and enable them to quickly integrate into the society. In the context of wireless communication, this article conducts the design and research of computer-assisted translation teaching courses based on embedded microprocessors, explores the use of high-tech system to train students in colleges and universities, and promotes the reform of college classrooms. This research is to use computers for assisted translation and embedded microprocessors for related calculations in translation teaching courses in colleges and universities, which can improve students’ learning efficiency to a certain extent. The experimental results show that the concentration of students in computer-assisted teaching is 20% higher than that of students in traditional teaching, and other related data are more than 8% higher. The teaching of computer-assisted translation courses benefits students greatly.

show abstract

Section: Embedded Operating Logic Of the Computer Hardwarementioning

confidence: 99%

Design and Research of Computer-Aided Translation Teaching Course under the Background of Embedded Microprocessor Wireless Communication

Yuan

Zhu

2022

Scientific Programming

View full text Add to dashboard Cite

show abstract

“…It will eventually lead to a wide range of failures, so it is an urgent need to diagnose and solve the failure in time [11]. Lv et al of the University of California, Los Angeles, proposed the construction of a new network expert system, which uses the learning and reasoning of artificial neural network to obtain network knowledge from the original data training, avoiding the cumbersome process from the network expert side avoiding the tedious process of acquiring knowledge from network experts [12]. e big data attribute selection method in distributed network fault diagnosis database was proposed by Chang et al through the support vector machine; the distributed network fault diagnosis database is deeply mined, the fault attribute weight is calculated, and the network fault is completed.…”

Section: Literature Reviewmentioning

confidence: 99%

Computer Communication Network Fault Detection Based on Improved Neural Network Algorithm

2022

Mobile Information Systems

View full text Add to dashboard Cite

In order to meet the new requirements of fault diagnosis response and intelligent degree in the current computer network, a fault detection of computer communication network based on an improved neural network algorithm is proposed. First, from the perspective of deep learning, based on the KDD99 data set, the network fault diagnosis method based on the convolutional neural network model is studied, and the data conversion operation of grayscale matrixed raw data is proposed. And experiments are carried out, the convolutional neural network structure is designed according to the scale of data features, a series of optimization studies including discarding learning, gradient optimization algorithm, and data enhancement based on this is carried out, and the establishment of the entire fault diagnosis model is completed. The experimental results show that, in the diagnostic model designed in this paper, the Tanh activation function is used in the first fully connected layer to achieve the best convergence speed. During the training process, it can start to converge after about 24 iterations, and the accuracy rate of the model training process can reach 98.1%, verifying the correctness and superiority of the algorithm and model.

show abstract

“…The development of computer technology and image recognition technology has made moving target detection technology more and more mature, and the use of unmanned aerial vehicles can make moving target detection technology to a higher level. This paper will use the moving target detection technology of UAV vision to study the vehicle traffic problem [14,15]. The five aspects of vehicle detection, vehicle tracking, vehicle violation behavior analysis, license plate positioning and recognition, and illegal vehicle information input data database are studied through algorithm calculation.…”

Section: Moving Target Detection Methods Based On Uav Visionmentioning

confidence: 99%

Moving Target Detection Technology Based on UAV Vision

Cheng¹,

Qin²,

Chen³

et al. 2022

Wireless Communications and Mobile Computing

View full text Add to dashboard Cite

The detection of moving objects by machine vision is a hot research direction in recent years. It is widely used in military, medical, transportation, and agriculture. With the rapid development of UAV technology, as well as the high mobility of UAVs and the wide range of high-altitude vision, the target detection technology based on UAV vision is applied to traffic management such as vehicle tracking and detection of vehicle violations. The moving target detection technology in this study is based on the YOLOv3 algorithm. It implements moving vehicle tracking by means of Mean-Shift and Kalman filtering. In this paper, the Gaussian background difference technology is used to analyze the illegal behavior of the vehicle, and the color feature extraction technology is used to identify and locate the license plate, and the information of the illegal vehicle is entered into the database. The experiment compares the moving target detection of UAV vision and the traditional target detection in four aspects: recognition accuracy, recognition speed, manual time, and divergent results. The results show that the average accuracy rates of UAV vision-based moving target detection and traditional pattern recognition are 98.4% and 87.8%, respectively. The recognition speeds are 24.9 (vehicles/sec) and 10.6 (vehicles/sec), respectively. However, the artificial time and divergence results of moving target detection based on UAV vision are only 1/3 of the traditional mode. The moving target detection based on UAV vision has a better moving target detection ability.

show abstract

Beyond 5G for digital twins of UAVs

Cited by 22 publications

References 29 publications

Design and Research of Computer-Aided Translation Teaching Course under the Background of Embedded Microprocessor Wireless Communication

Design and Research of Computer-Aided Translation Teaching Course under the Background of Embedded Microprocessor Wireless Communication

Computer Communication Network Fault Detection Based on Improved Neural Network Algorithm

Moving Target Detection Technology Based on UAV Vision

Contact Info

Product

Resources

About