scholarly journals Innovation Trend of Edge Computing Technology Based on Patent Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Hualei Ju ◽  
Lihua Liu
Keyword(s):  
Human Behavior ◽  
Recognition System ◽  
Fast Response ◽  
Edge Computing ◽  
Computing Technology ◽  
Low Energy Consumption ◽  
Software And Hardware ◽  
Computing Centers ◽  
Human Behavior Recognition ◽  
Communication Methods

Edge computing is an important foundation for building 5G networks, but in my country, there are few applications or inventions based on edge computing. In order to improve the application of edge computing, this article innovatively designs a human behavior recognition system based on a patent perspective, which provides a reference for other researchers. This paper discusses and designs the software and hardware schemes and related communication methods of a new edge computing framework that combines edge devices and cloud computing centers. After processing the collected human behavior data, the behaviors of the corresponding monitoring objects are classified and modeled, and then the distributed computing of edge devices is used to modify these models. These systems are characterized by low energy consumption and fast response. The experimental results prove. The recognition efficiency of edge computing technology from the patent perspective has been greatly improved. Its recognition speed is more than 30% faster than other algorithm calculations, and the accuracy of recognition reaches 0.852, which is about 20% higher than traditional recognition. The authors show that edge computing technology based on a patent perspective can play an important role in our lives.

scholarly journals Mobile Information System for English Teaching Based on Edge Computing and VR

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yanfang Zhou
Keyword(s):  
Human Behavior ◽  
Resource Sharing ◽  
Three Dimensional ◽  
Edge Computing ◽  
Computing Technology ◽  
Virtual Technology ◽  
Teaching Resources ◽  
English Teaching ◽  
Analysis System ◽  
Human Behavior Recognition

There are many difficulties in using cloud computing technology to solve this problem, and edge computing technology just provides an effective way to solve this problem. Changing from two-dimensional to three-dimensional will make education more realistic. This article uses the VR technology algorithm to design and analyze the English teaching system, combined with the current environment and requirements, in the construction of teaching resources, in order to clarify the direction in practical application. Secondly, according to the scene of human behavior recognition, a human behavior data collection, processing and analysis system based on edge computing is designed and implemented. And on the basis of detailed analysis of VR technology, the theoretical basis of VR technology applied to experiment teaching is discussed, and the development of virtual experiment is analyzed concretely using systematic teaching design ideas. VR technology greatly stimulates students’ learning motivation but also significantly improves their interest in learning. In addition, the application of virtual technology has greatly improved students’ learning enthusiasm. According to the findings of this article, based on the application of virtual reality technology, students’ English comprehension skills have increased by 19%, and the degree of resource sharing has increased by 11%.

Abnormal Behavior Recognition Based on Multi-Information Decision in Power Generation

2011 ◽  
Vol 121-126 ◽  
pp. 2482-2486
Author(s):  
Zhen Hua Wei ◽  
Xue Sen Li ◽  
Shi Bo Song ◽  
Le Zhang
Keyword(s):  
Power Generation ◽  
Human Behavior ◽  
Recognition System ◽  
Abnormal Behavior ◽  
Fisher Score ◽  
Behavior Recognition ◽  
Communication Device ◽  
Edge Detecting ◽  
Geometric Character ◽  
Human Behavior Recognition

So far most research of human behavior recognition focus on simple individual behavior, such as wave, crouch, jump and bend. This paper will focus on abnormal behavior with objects carrying in power generation. Such as using mobile communication device in main control room, taking helmet off during working and using umbrella in high place. In global environment, there are some almost fixed features for portable objects of workers, such as clothes. So we adopted edge detecting by color tracking to recognize object in worker. The sequence of 3D human behavior data would be expressed by geometric character of skeleton and its angle. Since specific time and space of behavior definition, it is of importance for recognition system using describing information in a comprehensive way. Take account of information complementary perspective, this paper introduced a method of making decision from multi-information by spatial pyramid and fisher score discretion for behavior recognition. And the method was proved to have advantages than some previous algorithms.

scholarly journals Research on Low-Power Main Control Chip Architecture Based on Edge Computing Technology

2021 ◽  
Vol 1802 (3) ◽  
pp. 032031
Author(s):  
Guoyu Cui ◽  
Wei Ye ◽  
Zhanbin Hou ◽  
Tong Li ◽  
Ruolin Liu
Keyword(s):  
Low Power ◽  
Edge Computing ◽  
Computing Technology

scholarly journals A Proximal Algorithm for Fork-Choice in Distributed Ledger Technology for Context-Based Clustering on Edge Computing

2020 ◽  
Vol 2 (1) ◽  
pp. 92
Author(s):  
Rahim Rahmani ◽  
Ramin Firouzi ◽  
Sachiko Lim ◽  
Mahbub Alam
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Edge Computing ◽  
Computing Technology ◽  
Proximal Algorithm ◽  
Data Intensive ◽  
Distributed Ledger ◽  
Smart Contract ◽  
Distributed Ledger Technology ◽  
Iot Devices

The major challenges of operating data-intensive of Distributed Ledger Technology (DLT) are (1) to reach consensus on the main chain as a set of validators cast public votes to decide on which blocks to finalize and (2) scalability on how to increase the number of chains which will be running in parallel. In this paper, we introduce a new proximal algorithm that scales DLT in a large-scale Internet of Things (IoT) devices network. We discuss how the algorithm benefits the integrating DLT in IoT by using edge computing technology, taking the scalability and heterogeneous capability of IoT devices into consideration. IoT devices are clustered dynamically into groups based on proximity context information. A cluster head is used to bridge the IoT devices with the DLT network where a smart contract is deployed. In this way, the security of the IoT is improved and the scalability and latency are solved. We elaborate on our mechanism and discuss issues that should be considered and implemented when using the proposed algorithm, we even show how it behaves with varying parameters like latency or when clustering.

3D Human behavior recognition based on binocular vision and face–hand feature

Optik ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4712-4717 ◽  
Author(s):  
Qing Ye ◽  
Junfeng Dong ◽  
Yongmei Zhang
Keyword(s):  
Human Behavior ◽  
Binocular Vision ◽  
Behavior Recognition ◽  
Human Behavior Recognition
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