Intelligent mobile information system for underground

Chumachenko, О. І.; Roshinsky, I. V.

doi:10.18372/1990-5548.51.11699

Cited by 1 publication

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“…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].…”

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

Mobile Information Systems

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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.

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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

Mobile Information Systems

View full text Add to dashboard Cite

show abstract

Intelligent mobile information system for underground

Cited by 1 publication

References 0 publications

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

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

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