Smart Public Security Police Big Data Visualization Analysis System Platform

The key to the visual analysis of police big data in the police system and the application of police analysis and judgment is to unearth the relationship between the five elements of personnel, organization, case (event), position and goods. If the five elements can be obtained with the help of IoT technology, then It will greatly improve the efficiency of the police in obtaining clues and information, while also avoiding human error. In the face of complex clue information, you can use big data analysis technology to realize in-depth and efficient mining and analysis.
Visualization plays a vital role in smart policing. It can help police workers better understand the structure and laws that may exist in the data. Visualization makes big data a key basis for decision-making.

Crime prevention, especially large-scale incidents, is an important part of public security work. Public security organs should use big data analysis as the premise to improve the level of "finding a needle in a haystack" from various intelligence, by extracting the temporal and spatial patterns and correlations of people's behavior, and relying on big data to conduct predictive analysis, command and control.
Crime prediction must be based on a full and objective grasp of the laws of crime and related factors. This requires a rigorous scientific spirit, respect for facts, accept reality, and obtain a crime objectively through a large number of investigations, studies and data analysis. The history and reality of the activities provide a reliable basis for crime prediction.
In the already formed pattern of big data, public security organs use the analysis and mining of big data to improve the foresight of their work, and realize the fusion processing and comparison of data, portrait models, fingerprints, text, pictures, audio, video and other data. Correct, differentiate, and maximize accurate analysis to achieve rapid linkage and precise strike. Improve the combat effectiveness of the entire public security system and respond effectively.

Yuanzhongrui ruiecjo police big data visualization analysis and actual combat platform functions mainly include case management, key personnel management, emergency command large-screen system, equipment management, social resource management and various actual combat applications for users to solve cases, including case series and parallel Collision analysis, trajectory analysis, multi-dimensional collision, deployment control and early warning functions are the core of the platform's visual display. It can be flexibly expanded according to changes in business needs, so as to quickly and easily help police officers understand the information embodied in the data.
Police big data collection is an important part of data application. The more comprehensive the police big data sources are, the more accurate intelligence analysis will be, the more precise command and dispatch, and the more efficient service deployment. In view of the chaotic resources, scattered information, incomplete data, unsatisfactory updates, and unfavorable support, it is first necessary to establish a complete police big data standard system. According to the data level, standardize the user's use rights, and implement strict security monitoring measures to realize the management and control of the full life cycle of big data, thereby providing reliable data protection for upper-level applications.
The intelligence research and judgment platform has an open, intensive and efficient intelligence research and judgment system. Yuanzhongrui Intelligent Public Security Analysis and Judgment Platform can deeply mine intelligence information through cloud data processing, realize intelligent prediction and processing, and provide decision-making support for managers to prevent, proactively respond, and accurately strike in advance. Centralized and unified management of the platform focuses on personnel key information, real-time collection of full trajectory data, after multi-mode comparison and early warning, real-time analysis and mining of early warning data are synchronized to implement the closed-loop operation of early warning information. Eventually, it will realize the "early warning of key personnel's abnormal kinetic energy and full control of the information of departing personnel", and build a sustainable, renewable and recyclable big data application ecosystem.