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.
关键词
物联网/高校/智慧管廊/控制/监测/预警
Key words
internet of things/universities/smart pipe gallery/control/monitor/early warning
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