文献类型：期刊文献

中文题名：智能校园安防监控物联网系统设计

英文题名：Design of Internet of Things system for intelligent campus security monitoring

作者：王谨毓[1]

机构：[1]华东理工大学,上海200237

年份：2019

卷号：42

期号：6

起止页码：51

中文期刊名：现代电子技术

外文期刊名：Modern Electronics Technique

收录：CSTPCD;;北大核心:【北大核心2017】；

语种：中文

中文关键词：智能校园;安防监控;物联网;异常情况;校园预警;模板匹配方法

外文关键词：intelligent campus;security monitoring;Internet of Things;abnormal situation;campus early-warning;template matching method

摘要：传统校园安防监控以人工巡逻为主,人工巡逻存在懈怠性,不具备数据分析与联动报警机制,大大降低了校园安防监控的可靠性。文中设计智能校园安防监控物联网系统,其包括感知层、网络及管理层、应用层,采用智能视频监控模块实时监控校园内的异常情况,将获取的异常情况上传至监控中心,监控中心根据现场情况通过门禁管理模块控制校园出入口行为。系统软件设计部分根据运动检测原理判别异常情况所在地和范围后,使用序贯相似性检测算法结合模板匹配方法判别异常情况的类别,实现校园预警。实验结果说明,所设计系统的综合关联度值为0.067 1,系统可靠性等级是1级,可靠性高。
The traditional campus security monitoring based on manual patrols has no data analysis and linkage alarm mechanism,and there exists slackness in manual patrols,which greatly reduces the reliability of campus security monitoring.Therefore,an Internet of Things(IoT) system for intelligent campus security monitoring is designed in this paper,which in-cludes the perceptual layer,network and management layer,and application layer. The intelligent video monitoring module is used to monitor the abnormal situations on campus in real time. The obtained abnormal situations are uploaded to the monitoring center,which controls the campus entrance and exit behaviors according to the site conditions by means of the access control management module. In the software design part of the system,the location and scope of the abnormal situations are judged ac-cording to the motion detection principle,and the types of the abnormal situations are judged by using the order similarity detec-tion algorithm in combination with the template matching method,so as to realize campus early-warning. The experimental re-sults show that the comprehensive correlation value of the designed system is 0.067 1,and the reliability level of the system is 1,which indicates a high reliability.