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基于物联网技术的智慧管廊实时自动监测与预警研究

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物联网技术的发展使得各类操作管理系统能够实现自动化和智能化管理.针对传统校园管廊系统中监测模块与异常预警模块存在的缺陷,研究首先利用物联网技术搭建了校园智慧管廊系统,接着采用递归优化下的主成分分析算法(Recursive-Principal Component Analysis,R-PCA)和Activiti流程引擎分别优化其监测模块与预警模块.实验结果表明,R-PCA算法改进后的监测系统能够达到95%以上的检测准确率,Activiti流程引擎下的异常预警系统则是能够达到92%左右的预警准确率,两个系统的误报率均在3%左右.综上,此次研究所搭建的校园管廊监测系统与预警系统均有较好的性能,可以应用于实际管廊监测问题中.
Research on Real Time Automatic Monitoring and Early Warning of Smart Pipe Corridors Based on Internet of Things Technology
The development of IoT technology enables various operational management systems to achieve automation and intelli-gent management.In response to the shortcomings of the monitoring module and anomaly warning module in traditional campus corri-dor systems,the study first utilized Internet of Things technology to build a campus smart corridor system,and then optimized its mo-nitoring module and warning module using Recursive Principal Component Analysis(R-PCA)algorithm and Activiti process engine,respectively.The experimental results show that the improved R-PCA algorithm in the monitoring system can achieve a detection ac-curacy of over 95%,while the anomaly warning system under the Activiti process engine can achieve a warning accuracy of about 92%,and the false alarm rates of both systems are around 3%.In summary,the campus pipe gallery monitoring system and early warning system built by the research institute have good performance and can be applied to practical pipe gallery monitoring problems.

internet of thingsuniversitiessmart pipe gallerycontrolmonitorearly warning

姚勇

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北京农业职业学院,北京 100072

物联网 高校 智慧管廊 控制 监测 预警

2024

自动化与仪器仪表
重庆工业自动化仪表研究所,重庆市自动化与仪器仪表学会

自动化与仪器仪表

CSTPCD
影响因子:0.327
ISSN:1001-9227
年,卷(期):2024.(2)
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