scholarly journals Analysis of the Evolution of Time and Space Differences and Coordinated Development Degree of Tourism Economy Based on Regional Internet of Things Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Su Zhang
Keyword(s):  
Internet Of Things ◽  
Influencing Factors ◽  
Employment Growth ◽  
Growth Mode ◽  
Time And Space ◽  
Causality Test ◽  
Multiple Indicators ◽  
Regional Tourism ◽  
Tourism Economy ◽  
Internet Of Things Technology

From the time dimension, this paper analyzes the characteristics of the scale, industrial structure, employment flexibility, and comprehensive employment effects of regional tourism employment based on the three-level criteria of the scope of tourism employment based on the regional Internet of Things. From the spatial dimension, we take the regional city as the basic research unit, adopt multiple indicators, and conduct a comprehensive evaluation of the regional development of regional tourism employment through horizontal and vertical comparisons. This paper uses multiple linear regression analysis to establish the relationship between the development level of the county tourism economy and the influencing factors; in order of magnitude of influence, they are tourism resource endowment, location traffic conditions, and economic development. Using a combination of a single indicator and multiple indicators, the county tourism economy is evaluated and analyzed for differences in time and space. We select the total tourism revenue as an indicator and use methods such as range, standard deviation, coefficient of variation, and coefficient to analyze the time difference of the tourism economy in each county. We adopt the Granger causality test and other methods to analyze the factors affecting tourism employment in the area and the growth mode. Through the establishment of a structural model of the tourism employment growth dynamics system, causality test and other methods are adopted to analyze the regional tourism employment influencing factors and growth methods, and the results show that the regional tourism employment growth mode is an investment-driven tourism employment growth mode.

E-Commerce Model Oriented to Cloud Computing and Internet of Things Technology

2021 ◽  
Vol 14 (2) ◽  
pp. 84-98
Author(s):  
Guanghai Tang ◽  
Hui Zeng
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Rapid Development ◽  
Distribution Functions ◽  
Competitive Environment ◽  
Enterprise Performance ◽  
Research Results ◽  
Multiple Indicators ◽  
Internet Of Things Technology

In recent years, the number of e-commerce netizen users in China has grown dramatically, and e-commerce users who shop online have also grown rapidly. In this competitive environment, the rapid development of e-commerce has also risen rapidly. Therefore, it is very necessary to actively carry out research on e-commerce models for cloud computing and internet of things technology. The purpose of this article is mainly to explore the research on e-commerce model for cloud computing and internet of things technology and establish a model for cloud computing and internet of things. It has data mining and distribution functions to test multiple indicators such as cloud computing facilities and enterprise performance. The research results show that the number of complaints on the e-commerce model based on cloud computing and internet of things technology is 2,368; the number of complaints on the B2B e-commerce model is 19,955; the number of complaints on the B2C e-commerce model is 5,016; the number of complaints in C2C e-commerce was 51,854.

Data collection of safety accidents in sports training of athletes with Internet of Things technology

2021 ◽  
pp. 1-7
Author(s):  
Zhiping Wang ◽  
Xinxin Zheng ◽  
Zhichen Yang
Keyword(s):  
Information Technology ◽  
Data Collection ◽  
Internet Of Things ◽  
The Internet ◽  
Sports Training ◽  
Accident Data ◽  
And Performance ◽  
Control Technologies ◽  
Internet Of Things Technology ◽  
The Internet Of Things

The Internet of Things (IoT) technology is an information technology developed in recent years with the development of electronic sensors, intelligence, network transmission and control technologies. This is the third revolution in the development of information technology. This article aims to study the algorithm of the Internet of Things technology, through the investigation of the hazards of athletes’ sports training, scientifically and rationally use the Internet of Things technology to collect data on safety accidents in athletes’ sports training, thereby reducing the risk of athletes’ sports training and making athletes better. In this article, the methods of literature research, analysis and condensing, questionnaire survey, theory and experiment combination, etc., investigate the safety accident data collection of the Internet of Things technology in athletes’ sports training, and provide certain theories and methods for future in-depth research practice basis. The experimental results in this article show that 82% of athletes who are surveyed under the Internet of Things technology will have partial injuries during training, reducing the risk of safety accidents in athletes’ sports training, and better enabling Chinese athletes to achieve a consistent level of competition and performance through a virtuous cycle of development.

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