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      Theoretical architecture design of a community risk prevention big data platform

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          Abstract

          Since communities are the basic units for public safety management, community risk prevention is of great significance. Community risk prevention must first identify community risks for people, things and management. This study analyzed the characteristics and causes of community risk to identify community risk prevention methods and how to monitor, control, predict, quickly detect and prevent community risk. Current international development trends for community risk prevention are reviewed to show that big data platforms are the key technology for community risk prevention. Finally, this paper describes the function, structure and construction of a large data platform for community risk prevention. This research on community risk prevention and big data platforms provides theoretical and technical support for community safety and security.

          Abstract

          摘要 社区是公共安全治理的基本单元, 社区安全研究意义重大。该文面向社区风险防范的重大需求, 首先, 从人、物及管理3个角度厘清社区风险的来源, 剖析社区风险的特性及原因; 然后, 阐述社区风险防范的内涵, 提出监测监控、预测预警和智能防范是社区风险防范的关键技术, 在综合分析当前风险防范研究现状及发展趋势的基础上, 指出大数据平台是社区风险防范的基础支撑; 最后, 分别从功能、结构及构建流程3个层面展开面向社区风险防范大数据平台的理论架构设计。为社区风险防范及大数据平台的基础理论研究大数据平台搭建及风险防范提供理论和技术支撑。

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          Author and article information

          Journal
          J Tsinghua Univ (Sci & Technol)
          Journal of Tsinghua University (Science and Technology)
          Tsinghua University Press
          1000-0054
          15 February 2019
          16 February 2019
          : 59
          : 2
          : 122-128
          Affiliations
          1Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China
          2Computer Network Information Center, Chinese Academy of Sciences, Beijing 100019, China
          3Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871, China
          Article
          j.cnki.qhdxxb.2018.26.052
          10.16511/j.cnki.qhdxxb.2018.26.052
          Copyright © Journal of Tsinghua University

          This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 Unported License (CC BY-NC 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See https://creativecommons.org/licenses/by-nc/4.0/.

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