Social Public Security Management in Intelligent City Based on Fast Big Data Analysis
- Tong Zhu
- Corresponding Author
- Tong Zhu
Available Online June 2018.
- https://doi.org/10.2991/ssme-18.2018.31How to use a DOI?
- Intelligent City;Grid management Fast Big Data Analysis; Social Public Security Management; Data Hierarchy and Knowledge Map Model;
- Social public security management is an important component in the current construction of intelligent cities in China. There have been scale construction of information system for social public security management, which has been widely applied, generating abundant information data in the city’s “grid” management process. However, in the actual construction process of intelligent city, due to the data conversion between various information systems and various restrictions for interconnection, further promotion and use of the social public security management has been seriously affected. In some big cities, every day there are tens of millions of new sensors collecting big data and store it for a long time. And it is difficult to meet the requirement of real-time management through the exchange between traditional information systems, urgently needing intelligent analysis and process to give full play to the application value. Taking solving “noise disturbance” as an example, introduces that the “Fast Big Data Analysis” method will dynamically realize the perception of social public security situation, performs predictive judgment and management guidance based on city-level data resource sharing and urban “grid” management, to effectively improve the overall management performance of the social public security management in the intelligent city.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Tong Zhu PY - 2018/06 DA - 2018/06 TI - Social Public Security Management in Intelligent City Based on Fast Big Data Analysis BT - Asia-Pacific Social Science and Modern Education Conference (SSME 2018) PB - Atlantis Press UR - https://doi.org/10.2991/ssme-18.2018.31 DO - https://doi.org/10.2991/ssme-18.2018.31 ID - Zhu2018/06 ER -