智能校园安防监控物联网系统设计
|
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.
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.
引文
[1]王畅,孙福明,李漾.基于物联网的多算法智能监护系统研究[J].电子技术应用,2017,43(11):7-10.WANG Chang,SUN Fuming,LI Yang.Research on multi-algorithm intelligent monitoring system based on the Internet of Things[J].Application of electronic technique,2017,43(11):7-10.
[2]黄伟,潘俊宇.分布式光纤预警系统在成品油管道安防中的应用[J].激光技术,2016,40(6):897-901.HUANG Wei,PAN Junyu.Application of distributed fiber optic warning system in the refined oil pipeline[J].Laser technology,2016,40(6):897-901.
[3]张茉莉,李艳霞.基于模式识别的全光纤周界安防系统[J].激光杂志,2017,38(10):65-68.ZHANG Moli,LI Yanxia.All fiber perimeter security system based on pattern recognition[J].Laser journal,2017,38(10):65-68.
[4]DEDIEU N,RHONE M,VIGOUROUX R,et al.Assessing the impact of gold mining in headwater streams of Eastern Amazonia using Ephemeroptera assemblages and biological traits[J].Ecological indicators,2015,52:332-340.
[5]刘业琦,吴治军,刘昌举,等.一种应用于安防监控的CMOS图像传感器的自动曝光算法研究[J].半导体光电,2017,38(2):283-287.LIU Yeqi,WU Zhijun,LIU Changju,et al.Study on an auto exposure algorithm applied in CMOS image sensor for security monitoring[J].Semiconductor optoelectronics,2017,38(2):283-287.
[6]FERNANDES F L,PICAN?O M C,FERNANDES M E S,et al.A new and highly effective sampling plan using attractantbaited traps for the coffee berry borer(hypothenemus hampei)[J].Journal of pest science,2015,88(2):289-299.
[7]蔡莹,杨伟,黄国兵.水力一体化治漂与枢纽库面安防系统研究及实施[J].水利水电技术,2017,48(11):168-173.CAI Ying,YANG Wei,HUANG Guobing.Study and implementation of hydraulic integrated floating debris control and reservoir surface security system for water control project[J].Water resources and hydropower engineering,2017,48(11):168-173.
[8]匡珍春,吴刘萍.基于物联网园林视觉监控方法研究与仿真[J].计算机仿真,2016,33(4):447-450.KUANG Zhenchun,WU Liuping.Monitoring method based on IoT garden vision research and simulation[J].Computer simulation,2016,33(4):447-450.
[9]马玉娟,杨国华,卫宁波,等.基于ARM-LabVIEW的家居安防监控系统的设计[J].电视技术,2015,39(11):108-112.MA Yujuan,YANG Guohua,WEI Ningbo,et al.Design of home security system based on ARM-LabVIEW[J].Video engineering,2015,39(11):108-112.
[10]YIN X C,LIU J.Research on the design of intelligent campus service APP:a case study of college students′reading APP[J].Art&design,2017(9):101-103.
[2]黄伟,潘俊宇.分布式光纤预警系统在成品油管道安防中的应用[J].激光技术,2016,40(6):897-901.HUANG Wei,PAN Junyu.Application of distributed fiber optic warning system in the refined oil pipeline[J].Laser technology,2016,40(6):897-901.
[3]张茉莉,李艳霞.基于模式识别的全光纤周界安防系统[J].激光杂志,2017,38(10):65-68.ZHANG Moli,LI Yanxia.All fiber perimeter security system based on pattern recognition[J].Laser journal,2017,38(10):65-68.
[4]DEDIEU N,RHONE M,VIGOUROUX R,et al.Assessing the impact of gold mining in headwater streams of Eastern Amazonia using Ephemeroptera assemblages and biological traits[J].Ecological indicators,2015,52:332-340.
[5]刘业琦,吴治军,刘昌举,等.一种应用于安防监控的CMOS图像传感器的自动曝光算法研究[J].半导体光电,2017,38(2):283-287.LIU Yeqi,WU Zhijun,LIU Changju,et al.Study on an auto exposure algorithm applied in CMOS image sensor for security monitoring[J].Semiconductor optoelectronics,2017,38(2):283-287.
[6]FERNANDES F L,PICAN?O M C,FERNANDES M E S,et al.A new and highly effective sampling plan using attractantbaited traps for the coffee berry borer(hypothenemus hampei)[J].Journal of pest science,2015,88(2):289-299.
[7]蔡莹,杨伟,黄国兵.水力一体化治漂与枢纽库面安防系统研究及实施[J].水利水电技术,2017,48(11):168-173.CAI Ying,YANG Wei,HUANG Guobing.Study and implementation of hydraulic integrated floating debris control and reservoir surface security system for water control project[J].Water resources and hydropower engineering,2017,48(11):168-173.
[8]匡珍春,吴刘萍.基于物联网园林视觉监控方法研究与仿真[J].计算机仿真,2016,33(4):447-450.KUANG Zhenchun,WU Liuping.Monitoring method based on IoT garden vision research and simulation[J].Computer simulation,2016,33(4):447-450.
[9]马玉娟,杨国华,卫宁波,等.基于ARM-LabVIEW的家居安防监控系统的设计[J].电视技术,2015,39(11):108-112.MA Yujuan,YANG Guohua,WEI Ningbo,et al.Design of home security system based on ARM-LabVIEW[J].Video engineering,2015,39(11):108-112.
[10]YIN X C,LIU J.Research on the design of intelligent campus service APP:a case study of college students′reading APP[J].Art&design,2017(9):101-103.