Security fault diagnosis system and method based on Internet of Things

Abstract

The invention provides a security fault diagnosis system and method based on Internet of Things, an intelligent transmission case is arranged between a front-end intelligent device and a back-end processing center, a first fault diagnosis is performed on the front-end intelligent device by the intelligent transmission case, a power source of the front-end intelligent device can be cut immediately when a major fault occurs, the back-end processing center performs a further fault diagnosis when the major fault does not occur, so that the speed of fault diagnosis is improved, and the burden of the back-end processing center is reduced; besides, the system and the method can monitor and perform fault diagnosis on the working conditions of the intelligent transmission case and the front-end intelligent device, thereby more reliably ensuring normal operation of the front-end intelligent device. According to the invention, the front-end intelligent device with fault can be diagnosed in real time without the user performing an on-site inspection tour, a power supply can be cut remotely and automatically, and the user can be informed that the fault can be pointedly maintained in first time, so that the safety and reliability of the security monitoring system are ensured.

Description

technical field [0001] The present invention relates to the field of security technology, and more specifically, to a security fault diagnosis system and method based on Internet of Things technology. Background technique [0002] The security monitoring system is aimed at preventing and combating illegal crimes. Security monitoring systems are set up in complex public security places, key locations, main streets, places where cases frequently occur, important intersections, checkpoints, etc., and video surveillance images are transmitted to public security at all levels in real time. Government agencies and other relevant departments, through the browsing and recording of image information, enable public security organs at all levels and other relevant departments to intuitively understand and grasp the security dynamics in the monitoring area, and timely and effectively improve the level of social security management. [0003] As we all know, cameras and optical transceive...

AI Technical Summary

Problems solved by technology

[0005] 1. Send the various parameters of the front-end intelligent equipment measured by the sensor to the background processing center, all of which are processed by the background processing center, which not only increases the burden on the background processing center, but also prolongs the time for judging failures. When a serious failure occurs in the equipment, it cannot be dealt with immediately;

[0006] 2. Only the front-end smart devices are monitored, but the devices that supply power to the front-end smart devices are not monitored. In this way, when the power supply equipment fails, the front-end smart devices will not work properly;

[0007] 3. Existing fault detection systems do not take into account the type and severity of faults in front-end intelligent equipment. Some use simple threshold judgment methods to detect faults, and some use modeling algorithms that are too complex to be conducive to real-time detection. The performance requirements of fault detection equipment are relatively high;

[0008] 4. The front-end smart devices directly send the status data collected by the sensor to the back-end processing center through the network. Since the unprocessed status data contains a lot of noise, it not only increases the burden on the network and the back-end processing center, but also affects the accuracy of fault judgment. Accuracy;

[0009] 5. All front-end equipment failures must be handled on site, which increases maintenance costs

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