Background of the plan
Public security big data has become a trend and focus of current public security informationization work. The construction of public security big data currently faces problems such as "scattered and unshared data", "mixed and non-standard data", and "too much data, too little application", which have not truly released the value of data. According to the requirements of the Ministry of Public Security, we should follow the overall requirements of unified operation network, unified infrastructure, unified data resources, unified service platform, unified security strategy, and unified standard specifications, accelerate the construction and application of intelligent public security big data, focus on building a new ecosystem of intelligent application of public security big data, and promote the evolution of sweat policing to intelligent policing. Accelerate data fusion, break down data silos, and form a data information resource service system with full police coverage and coordinated utilization.
Plan Introduction
Plan Introduction
The application and construction of public security and police big data are carried out on the Public Security Information Network, and data governance is carried out on both the Video Private Network and the Public Security Information Network. The Video Private Network mainly handles IoT data governance, while the Public Security Information Network mainly handles business data governance and IoT data fusion analysis.
Public security and police big data comply with the "Public Security Big Data Specification Document" (4 volumes in total), benchmarking the content of volumes 1-2 of the specification document, with basic benchmarking in functionality and differences in interface definition. At the same time, adding chapters on big data applications is aimed at showcasing the value of big data.
Product advantages
1.The application of police big data is mainly based on the public security information network, constructing three categories of general applications, thematic applications, and visual applications to solve the problem of insufficient application depth and achieve data empowerment of police.
2. Promote the precision of dynamic evaluation through source governance, and promote the scientificity of construction through evaluation, forming an effective closed loop of construction, governance, and evaluation.
3.Based on the algorithm warehouse system, achieve unified management and scheduling of resources such as algorithms, computing power, data, and services.
4. Data supports cross level and cross network exchange, and flows to the places where the application needs it on demand, solving the problem of data silos.
5.Strengthen the classification and governance capabilities of IoT data and business data, improve data quality, and effectively integrate various data assets.
6.Based on a unified cloud platform, cloud computing technologies such as virtualization and containers are adopted to achieve unified management, on-demand storage, and dynamic scheduling of computing and storage resources.
