School of Education and Modern Art, Shangqiu Institute of Technology, Shangqiu, Henan 476000, China.
Comput Intell Neurosci. 2022 Feb 12;2022:3567697. doi: 10.1155/2022/3567697. eCollection 2022.
Based on the news and public opinion multioutput Internet of Things architecture, this article analyzes and predicts its popularity with big data. Firstly, the model adopts a three-tier architecture, in which the bottom layer is the data layer. It is mainly responsible for the collection of the terminal sensor data of the Internet of Things, and it uses intelligent big data as the data warehouse. Secondly, the computing layer on the data layer mainly provides the computing framework. Using the open-source SQL query engine, a cluster environment based on memory computing is constructed to realize the parallelization of data computing. It is used for interactive operations between the system and users. It receives and forwards the query requests submitted by the client browser, transmits them to the server cluster for execution, and displays the results in the browser. The end is displayed to the user. After that, combined with the needs of the development and application of news and public opinion big data, the data collection process was analyzed and designed, and the distributed data collection architecture was built. The intelligent Internet of Things was adopted for data storage, the data storage structure was analyzed and designed, and the data storage structure was designed to avoid catching. The repeat check algorithm is used to repeatedlystore the obtained page data. At the same time, according to the analysis of the business needs of the news and public opinion information platform, the overall functional structure of the platform was designed. The database and platform interface were designed in detail. The simulation results show that the model realizes the statistical query of the collected sensor alarm information and historical data on the user system, combines the historical operating data to analyze the relationship between the supply/return water temperature of the heat exchange station and the outdoor temperature, and realizes chart visualization of data analysis.
基于新闻和公共舆论多输出物联网架构，本文利用大数据对其流行度进行分析和预测。首先，该模型采用三层架构，底层为数据层，主要负责物联网终端传感器数据的采集，使用智能大数据作为数据仓库。其次，数据层上的计算层主要提供计算框架。使用开源 SQL 查询引擎构建基于内存计算的集群环境，实现数据计算的并行化，用于系统与用户之间的交互操作。它接收并转发客户端浏览器提交的查询请求，将其发送到服务器集群执行，并在浏览器中显示结果。最后，结合新闻和公共舆论大数据的发展和应用需求，对数据采集过程进行分析和设计，构建分布式数据采集架构。采用智能物联网进行数据存储，分析和设计数据存储结构，设计数据存储结构以避免重复检查算法用于重复存储获取的页面数据。同时，根据新闻和舆论信息平台的业务需求分析，对平台的整体功能结构进行设计，详细设计数据库和平台接口。仿真结果表明，该模型实现了对用户系统采集的传感器报警信息和历史数据的统计查询，结合历史运行数据，分析换热站供回水温度与室外温度之间的关系，并实现数据分析的图表可视化。
