Fire safety alarm system for high-rise buildings based on machine vision

Qinghua Liu; Wenhong Yu; Songling Zou; Kuan Wang

doi:10.1117/12.3028974

22 May 2024 Fire safety alarm system for high-rise buildings based on machine vision

Qinghua Liu, Wenhong Yu, Songling Zou, Kuan Wang

Proceedings Volume 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023); 131761Q (2024) https://doi.org/10.1117/12.3028974
Event: Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 2023, Hangzhou, China

Abstract

Due to safety hazards, many residential buildings have restricted the entry of electric bicycles and chargers into the building. However, the phenomenon of electric bicycles entering the elevator in violation of regulations often occurs. This article develops a machine vision based electric bicycle detection and recognition algorithm, which uses the original image of the electric bicycle as input to the neural network and designs a feature extraction algorithm. This algorithm utilizes the external morphological features of electric bicycles to filter out interference and intelligently analyze and accurately distinguish interfering objects. And combined with pressure sensing technology to determine the precise position of electric bicycles in elevators, complete automatic detection and recognition. Embed the algorithm into the internal camera of the elevator, intelligently monitor the electric bicycles inside the elevator, and achieve detection, analysis, and recognition of the electric bicycles. As long as the camera inside the elevator detects that an electric bicycle has entered the elevator, it will immediately issue a warning of "electric bicycles no enter", and the elevator door will remain opening. Only by pushing the electric bicycle out of the elevator door can it operate normally. This function solves the problem of electric bicycles going upstairs in high-rise buildings from the source, greatly reducing safety hazards.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qinghua Liu, Wenhong Yu, Songling Zou, and Kuan Wang "Fire safety alarm system for high-rise buildings based on machine vision", Proc. SPIE 13176, Fourth International Conference on Machine Learning and Computer Application (ICMLCA 2023), 131761Q (22 May 2024); https://doi.org/10.1117/12.3028974

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KEYWORDS

Buildings

Image processing

Safety

Detection and tracking algorithms

Cameras

Machine vision

Infrared radiation

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