An Empirical Study on Response to Online Customer Reviews and E-Commerce Sales: From the Mobile Information System Perspective

With the development of mobile information, artificial intelligence technology has developed rapidly, which is changing everything in our life. Meanwhile, smart education appeared and attracted much attention; however, there is still a lack of systematic discussion on how to take the road of artificial intelligence plus smart classroom. In order to promote the intelligent development of education, this article mainly talks about the application of artificial intelligence technology to college English smart classrooms. In the process of teaching, a new teaching model of college English smart classroom was designed, and the teaching model was carried out through the experimental class and the survey results of the students. The survey results show that students’ satisfaction with this teaching model is as high as 80%.

Section: Related Contentmentioning

confidence: 99%

College English Smart Classroom Teaching Model Based on Artificial Intelligence Technology in Mobile Information Systems

Zhang

Chen

2021

“…In order to be compatible with most external devices, the most advanced devices provide various forms of hardware interfaces, such as UART, USB, and wireless transmission interfaces [9]. When there are many sensors sending data to the most advanced equipment [10], whether it is physical data or network data, it must be cleared by the data processing unit inside the device [11,12]. After that, the data are uploaded to the cloud in a predefined format [13,14].…”

Section: The Methods Of Continuous Use Behavior Of Knowledge Payment Platform Based On Edge Computing Under Mobile Information Systemmentioning

confidence: 99%

Continuous Use Behavior of Knowledge Payment Platform Based on Edge Computing under Mobile Information System

Huo

2021

From 2015 to the end of 2016, the Internet set off a wave of payment for knowledge. Pay-for-knowledge platforms such as Fenda, iGet, and Qianliao went online quickly, and platforms such as Himalaya FM, Zhihu, and Qingting FM gathered to launch paid columns. The number of users increased rapidly, and payment for knowledge was considered to have reached the trend of development. This article aims to study the introduction of edge computing in the mobile information system into the existence and inevitability of the knowledge payment platform; analyze the advantages, dilemmas, and optimization paths of the knowledge payment platform; and try to provide a theoretical reference for promoting its development. This article puts forward an explanation of the related content of mobile edge computing and RFID technology overview, using comparative experiment and behavior analysis methods. The experimental results show that there are 98 people under the age of 18 in the questionnaire, accounting for 19.1% of the total, 201 people aged 18–29, accounting for 39.1% of the total, 142 people aged 30–39, accounting for 27.6% of the total, and 73 people over 40 years old, accounting for 14.2% of the total number. It can be seen from the data that the sample age is mainly concentrated in the 18–29 years old, followed by the 30–39 years old; the sample age is biased towards young people. It has well completed the continuous use behavior analysis of the knowledge payment platform based on edge computing under the mobile information system.

“…must be designed and constructed with high reliability to improve the safety and reliability of the entire digital community computer network and application system (5) Scalability: the construction of the digital community needs to be gradually and continuously expanded. For this reason, the system needs to adopt component technology to support the combination, inheritance, and online definition of applications [25] 3.3. Module Function Design of the System.…”

Section: System Design Principlesmentioning

confidence: 99%

Digital Community Management Mobile Information System Based on Edge Computing

2021

Edge computing refers to an open platform that integrates network, computing, storage, and application core capabilities on the side close to the source of things or data and provides nearest-end services nearby. “Digital Community” refers to the use of various information technologies and methods to integrate community resources and build a network platform for interactive exchanges and services between the government, property service agencies, residents, and various intermediary organizations within the community. In order to reduce the management tasks of community managers, reduce their community management burden, and improve the management efficiency of community managers, this article is based on the description of several keywords such as distributed edge computing, edge computing business usage scenarios, and digital community management. Edge computing technologies such as centralized traffic model and attribute-based trust evaluation avoid waste of network resources, reduce time delay and system energy consumption, and improve system operation efficiency. A digital community management mobile information management system is designed and developed. 102 owners of the community conducted visits and questionnaire surveys. After investigation and research, it was found that this system has good performance, meets the management needs of most communities, and can improve the management efficiency of community managers by 4%–6%; it has also improved community residents’ satisfaction with digital community management by 2-3%.