Fault marking method based on networked video monitoring

Abstract

The invention relates to the field of security monitoring and particularly to a fault marking method based on networked video monitoring. A networked alarm system codes each camera which has an intelligent video analysis function. When the system finds that one of the cameras gives the same alarms for multiple times in a short period of time, a server center determines that the received alarms are all false alarms, and when the false alarm frequency reaches a threshold, the camera generating the false alarms is marked as a fault, the same camera at the front end is prevented from reporting alarms of the same type to the service center in a subsequent period of time, and meanwhile, related maintenance staff are notified to eliminate the fault in time; or the system waits until situations such as rainy days pass; and then a normal processing flow is recovered. The beneficial effects are as follows: through building a repeated alarm filtering and device fault notification mechanism on the network server, operators are librated from meaningless repetitive work and can provide service for real alarms; and meanwhile, technical maintainers are informed about device fault status in time and can review the cameras marked as faults on time, in case the cameras are forgotten and thus real alarms are missed.

Description

technical field [0001] The invention relates to the field of security monitoring, in particular to a fault calibration method based on networked video monitoring. Background technique [0002] Networked alarm service is the mainstream security service, among which video networked service can help customers watch their homes and stores, etc. Patent application 201310311758.2 describes an implementation method of Huirui Tianyan. One of the main tasks of this service architecture is that the front-end video analysis equipment captures the video alarm and reports it to the network server. The network server records and forwards it to the on-duty service center personnel for manual identification and follow-up processing. At the same time, it also monitors the equipment work at the user end. state, to ensure that it will be detected in time when it fails, and the fault will be eliminated in time to ensure safety. [0003] A common fault in this process is that in snowy and rainy...

AI Technical Summary

Problems solved by technology

[0003] A common fault in this process is that in snowy and rainy days, the camera will capture a lot of false alarm images, some because the lens is splashed by water, some because the lens is tilted after being slapped by a shaking branch, and the infrared camera is caught by a spider web. Interference caused by many flying insects at night after the threading, unstable power supply of the camera and distortion of the image due to interference, etc., will cause the front-end video analysis equipment to continuously report alarms or video abnormalities, requiring the service center to manually confirm and intervene, making the service center When people receive the same type of alarms from the same place for a long time and require identification and processing, their attention will be continuously occupied, a lot of ineffective work will be done, and the real alarm situation in other places may be missed.

At the same time, most of the cameras that have the above situation can no longer provide clear and effective video images, and need to be repaired manually

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