Big data analysis based trapping in elevator misinformation identification method

Abstract

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.

Description

technical field [0001] The invention relates to the field of big data analysis, in particular to a method for using big data analysis to judge the false alarm recognition of elevator trapped people. Background technique [0002] At present, elevators, especially straight elevators, have become the standard equipment of many residential buildings, office buildings, and shopping malls. While it brings a lot of convenience to the lives of the people, it will also be caused by many factors such as inadequate maintenance or human misuse. , resulting in frequent incidents of trapped people in straight ladders. Since the daily maintenance of elevators for daily cleaning, advertising and operation and maintenance personnel will cause considerable trapped people alarms, it is particularly important to establish a complete and real-time system for eliminating false alarms for elevator trapped people. At present, the way for the elevator maintenance unit to monitor the trapped people ...

AI Technical Summary

Problems solved by technology

[0004] The shortcoming of this technical scheme: this scheme is mainly aimed at the logic combination between a plurality of detection signals of one-step elevator to detect whether described elevator is in sleepy state, and the required signal is more, when wherein there is signal break down (such as acceleration Sensor failure, etc.), will lead to missed alarms, and at the same time, due to the series processing of multiple signals, it will also have a great impact on the real-time performance of alarm processing for trapped people; at the same time, in order to ensure higher accuracy, multiple expensive Sensing (including acceleration sensor, PIR infrared sensor, etc.) to obtain accurate elevator status signals, so the cost of the detection system is also relatively high

Images