Sub-system model for data collection and distributed sensing search technique for Internet of Things applications

The application degree and application scope of 5G Internet of Things technology and big data analysis technology are becoming wider and wider, bringing opportunities for the development of traditional enterprises and providing technological innovation support for the development of new enterprises. Based on 5G Internet of Things technology and big data technology, this paper designs and studies an intelligent agricultural monitoring platform. We collect crop growth data and monitor crop growth status through this platform to study the 5G-oriented IoT big data analysis method system. This paper studies the data collection and storage issues involved in the huge agricultural IoT data environment. This article analyzes the specific sources of agricultural big data, the specific methods of data collection, and the methods of various database storage technologies. Combining wireless sensor network technology, large-source data processing technology, and distributed data storage technology, a method is proposed to solve the problem of rural Internet data collection and storage in the big data environment. This paper proposes a spatiotemporal block processing TSBPS to store the first detection data. The method uses spatiotemporal preblocking, data compression, and caching to significantly improve the recording speed of near real-time storage and microdetection data. In the experimental part of this article, experiments are carried out on the key parts of the IOT-HSQM system model that may limit storage or query performance. Experimental results show that this article compares TSBPS and direct writing methods. The maximum write speed increased by 79%, and the average write speed increased by 42%. The IOT-HSQM system model can meet the requirements of compiling and query performance and statistical analysis.

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Model of Data Collection Control in the Internet of Things on the Basis of Social Network Technologies

Journal of Physics Conference Series ◽

10.1088/1742-6596/1864/1/012093 ◽

2021 ◽

Vol 1864 (1) ◽

pp. 012093

Author(s):

N A Zhukova ◽

A M Thaw ◽

E L Evnevich

Keyword(s):

Social Network ◽

Data Collection ◽

Internet Of Things ◽

The Internet ◽

Network Technologies ◽

The Internet Of Things

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Data Collection Method of Space-based Internet of Things Based on Layered Fountain Code

2020 IEEE 6th International Conference on Computer and Communications (ICCC) ◽

10.1109/iccc51575.2020.9345266 ◽

2020 ◽

Author(s):

Yiqi Xue ◽

Zhiyu Sun ◽

Zhongjun Liang ◽

Cunqun Fan ◽

Xiaobin Xu

Keyword(s):

Data Collection ◽

Internet Of Things ◽

Collection Method ◽

Data Collection Method ◽

Fountain Code

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Joint Flight Cruise Control and Data Collection in UAV-aided Internet of Things: An Onboard Deep Reinforcement Learning Approach

IEEE Internet of Things Journal ◽

10.1109/jiot.2020.3019186 ◽

2020 ◽

pp. 1-1

Author(s):

Kai Li ◽

Wei Ni ◽

Eduardo Tovar ◽

Mohsen Guizani

Keyword(s):

Reinforcement Learning ◽

Data Collection ◽

Internet Of Things ◽

Learning Approach ◽

Cruise Control

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

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219100 ◽

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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Traffic Flow Data Collection and Signal Control System Based on Internet of Things and Cloud Computing

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.846-847.1608 ◽

2013 ◽

Vol 846-847 ◽

pp. 1608-1611 ◽

Cited By ~ 1

Author(s):

Hui Jie Ding

Keyword(s):

Cloud Computing ◽

Control System ◽

Data Collection ◽

Internet Of Things ◽

Traffic Flow ◽

Signal Control ◽

Traffic Signal Control ◽

Flow Data ◽

Traffic Jam ◽

Sensing Data

As more and more cars are in service, the traffic jam becomes a serious problem in our society. At the same time, more and more sensors make the cars more and more intelligent, and this promotes the development of Internet of things. Real time monitoring the cars will produce massive sensing data, the Cloud computing gives us a good manner to solve this problem. In this paper, we propose a traffic flow data collection and traffic signal control system based on Internet of things and the Cloud computing. The proposed system contains two main parts, sensing data collection and traffic status control subsystem.

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Towards Self-Awareness Privacy Protection for Internet of Things Data Collection

Journal of Applied Mathematics ◽

10.1155/2014/827959 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 8

Author(s):

Kok-Seng Wong ◽

Myung Ho Kim

Keyword(s):

Data Collection ◽

Internet Of Things ◽

Personal Data ◽

Self Awareness ◽

Privacy Concern ◽

Goods And Services ◽

Data Collector ◽

Inaccurate Data ◽

Secure Protocol ◽

The Internet Of Things

The Internet of Things (IoT) is now an emerging global Internet-based information architecture used to facilitate the exchange of goods and services. IoT-related applications are aiming to bring technology to people anytime and anywhere, with any device. However, the use of IoT raises a privacy concern because data will be collected automatically from the network devices and objects which are embedded with IoT technologies. In the current applications, data collector is a dominant player who enforces the secure protocol that cannot be verified by the data owners. In view of this, some of the respondents might refuse to contribute their personal data or submit inaccurate data. In this paper, we study a self-awareness data collection protocol to raise the confidence of the respondents when submitting their personal data to the data collector. Our self-awareness protocol requires each respondent to help others in preserving his privacy. The communication (respondents and data collector) and collaboration (among respondents) in our solution will be performed automatically.

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