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73 results about "Alarm filtering" patented technology

Big data analysis based trapping in elevator misinformation identification method

InactiveCN110790101ACausing distressCause wasteElevatorsThe InternetFilter analysis
The invention relates to a big data analysis based trapping in an elevator misinformation identification method, and provides an alarming method when someone is trapped in an elevator based on the bigdata acquired by a sensor during the actual running of the elevator and combining the characteristics of the running big data of complicated equipment with the machine analysis theory. The method includes the steps of: establishing a deep neural network predication model; acquiring signals by an alarming service unit, and performing processing and analysis to the data; judging whether it is suspected trapped alarming, or not; if yes, sending the alarming information to the trapped alarming filtering service unit of the Internet of Things; performing real-time filtering analysis on the alarming based on the trapped alarming filtering service unit of the Internet of Things; judging whether someone is really trapped, or not according to the analysis result; and if someone is really trapped,feeding the trapped alarming information back to the alarming service unit, and informing the alarming information to a maintenance department by the alarming service unit, and meanwhile, starting theinformation storage service unit for information storage. According to the method, whether someone is really trapped can be distinguished in real time, and the trapped information can be informed inreal time and assistance can be given to the maintenance department, so that the trapped passenger can be rescued timely.
Owner:虏克电梯有限公司

System and method of filtering false alarm of person-trapped-in-elevator condition in real time based on time domain relational network

InactiveCN110002303ASoothe in real timeReal-time guidanceElevatorsTime domainVideo storage
The invention discloses a system and method of filtering false alarm of a person-trapped-in-elevator condition in real time based on a time domain relational network. The system comprises an alarm service unit, a video storage service unit and a person-trapped-in-elevator condition alarm filter service unit based on the time domain relational network. The alarm service unit acquires an image and processes and analyzes the image data to judge whether suspected person-trapped-in-elevator alarm is available or not, and if so, the alarm service unit sends alarm information and an alarm video to the person-trapped-in-elevator condition alarm filter service unit based on the time domain relational network; the person-trapped-in-elevator condition alarm filter service unit based on the time domain relational network filters and analyzes the alarm video in real time and judges whether a true person-trapped-in-elevator condition happens or not according to the analyzing result, and if so, the person-trapped-in-elevator condition alarm filter service unit feeds the person-trapped-in-elevator alarm information back to the alarm service unit; and the alarm service unit informs a maintenance part with the alarm information and the video storage service unit is started to store the video. The system and the method can differentiate whether the true person-trapped-in-elevator condition happens or not in real time and inform and assist the maintenance unit in real time to rescue trapped passengers immediately.
Owner:ZHEJIANG NEW ZAILING TECH CO LTD

Fault marking method based on networked video monitoring

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.
Owner:深圳辉锐天眼科技有限公司
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