News and Public Opinion Multioutput IoT Intelligent Modeling and Popularity Big Data Analysis and Prediction

Abstract

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.