Device and method for detecting electric bicycle attempting to enter elevator

Abstract

The invention discloses a device and a method for detecting an electric bicycle attempting to enter an elevator. The device comprises an electric bicycle detection algorithm module A, a module B for detecting and judging whether to start the electric bicycle detection algorithm module A, a module C for outputting a primary alarm message, a module D for checking primary alarm message information and performing analysis to make secondary judgment and outputting a secondary alarm message, and a module E for receiving secondary alarm results and processing; the module B analyzes the current stateof the elevator and judges whether the electric bicycle detection operation can be started, if yes, the module A is started, the module A detects whether the electric bicycle exists in the field of view, if the electric bicycle is detected, the module C is started, the module C outputs a primary alarm message and / or a program running state information, and the module D analyzes the output information and judges whether the alarm information and the association information of the secondary judgment result are sent out to the outside or not.

Description

technical field [0001] The invention belongs to the field of elevator detection, and in particular relates to a device and method for detecting an electric bicycle trying to enter an elevator. Background technique [0002] Fires caused by electric bicycles continue to occur. It is very important to prevent electric bicycles from entering buildings, especially high-rise buildings. The detection of electric vehicles at the elevator entrance is based on this demand. This need has a product form, namely a camera with image electric bicycle detection algorithm. Such a product must simultaneously meet four criteria before it can be deployed at scale: local operation, low cost, accurate detection, and remote viewing. [0003] In the past, video-based detection methods had a large number of false positives. Even with advanced deep learning algorithms, because of various installation scenarios, 24 hours a day operation, second-level detection and alarm delay requirements, even a ver...

AI Technical Summary

Problems solved by technology

[0003] In the past, video-based detection methods had a large number of false positives. Even with advanced deep learning algorithms, because of various installation scenarios, 24 hours a day operation, second-level detection and alarm delay requirements, even a very low detection error The positive rate will also bring a large number of false positives