当前位置: X-MOL 学术Mob. Inf. Syst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
5G-Oriented IoT Big Data Analysis Method System
Mobile Information Systems ( IF 1.863 ) Pub Date : 2021-09-14 , DOI: 10.1155/2021/3186696
Lei Hu 1, 2 , Xianling Xia 2, 3
Affiliation  

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.

中文翻译:

面向5G的物联网大数据分析方法体系

5G物联网技术和大数据分析技术的应用程度和应用范围越来越广,为传统企业的发展带来机遇,也为新兴企业的发展提供技术创新支持。本文基于5G物联网技术和大数据技术,设计并研究了一个智能农业监控平台。我们通过该平台采集作物生长数据,监测作物生长状况,研究面向5G的物联网大数据分析方法体系。本文研究了庞大的农业物联网数据环境中涉及的数据采集和存储问题。本文分析了农业大数据的具体来源,数据收集的具体方法,以及各种数据库存储技术的方法。结合无线传感器网络技术、大源数据处理技术、分布式数据存储技术,提出了一种解决大数据环境下农村互联网数据采集和存储问题的方法。本文提出了一种时空块处理TSBPS来存储第一次检测数据。该方法使用时空预分块、数据压缩和缓存,显着提高了近实时存储和微检测数据的记录速度。在本文的实验部分,对IOT-HSQM系统模型中可能限制存储或查询性能的关键部分进行了实验。实验结果表明,本文比较了TSBPS和直写方法。最大写入速度提升79%,平均写入速度提高了42%。IOT-HSQM系统模型可以满足编译查询性能和统计分析的要求。
更新日期:2021-09-14
down
wechat
bug