信息网络安全 ›› 2019, Vol. 19 ›› Issue (12): 1-9.doi: 10.3969/j.issn.1671-1122.2019.12.001

• 等级保护 • 上一篇    下一篇

面向敏感区域的智能监控与预警数据库研究与设计

王文明1(), 王全玉1, 王英豪2, 任好盼1   

  1. 1.北京理工大学计算机学院,北京 100081
    2.北京理工大学设计与艺术学院,北京 100081
  • 收稿日期:2019-06-20 出版日期:2019-12-10 发布日期:2020-05-11
  • 作者简介:

    作者简介:王文明(1967—),男,北京,副教授,硕士,主要研究方向为信息安全、虚拟现实与增强现实、区块链技术等;王全玉(1968—),男,黑龙江,副教授,博士,主要研究方向为移动增强现实、机器人技术、人机交互技术;王英豪(1999—),男,北京,本科,主要研究方向为人机交互技术、工业产品设计与开发;任好盼(1995—),男,河南,硕士研究生,主要研究方向为人机交互技术、图形图像处理技术。

  • 基金资助:
    国家自然科学基金[71834001]

Research and Design of Intelligent Monitoring and Early Warning Database System for Sensitive Areas

Wenming WANG1(), Quanyu WANG1, Yinghao WANG2, Haopan REN1   

  1. 1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
    2. School of Design and Arts, Beijing Institute of Technology, Beijing 100081, China
  • Received:2019-06-20 Online:2019-12-10 Published:2020-05-11

摘要:

文章采用多线程、数据库、目标检测与跟踪、区块链等技术设计了适合敏感区域使用的智能监控与预警数据库系统,实现了对可疑动态物体和静态物体的定位、检测、跟踪、拍摄、入库、预警、查询、管理等功能,解决了监控编程中经常出现的“死机”等问题。同时,为了保证监控预警数据的高度安全性,文章利用区块链技术存储相关数据,由共识算法决定数据的删除等操作,并对关键技术和实现过程进行分析,对视频流畅度等进行实验验证。文章以“双一流”高校实验室安全建设为例对设计的智能监控与预警数据库系统进行了验证。

关键词: 智能监控, 预警, 区块链, 数据库, 敏感区域

Abstract:

This paper analyzes and practices the intelligent monitoring and early warning in the sensitive area, designs the intelligent monitoring and early warning system suitable for the sensitive area by using multithreading, database, target detection and tracking, blockchain and other technologies, and realizes the positioning, detection, tracking, shooting, warehousing, early warning, query, management of suspicious dynamic and static objects, solves the “crash” and other problems in monitoring programming. In order to ensure the high security of monitoring and early warning data, this paper discusses the storage of relevant data by blockchain technology, determines the deletion of data by the consensus algorithm, describes the key technology and implementation process, and carries out experimental verification and analysis of video fluency. This paper takes the safety construction of “double first class” university laboratory as an example to verify the system.

Key words: intelligent monitoring, early warning, block chain, database, sensitive areas

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