Real‐time intelligent fire identification and early warning method based on campus surveillance video
Year: 2025
Type: article
Abstract: In recent years, campus fire incidents have become frequent, significantly impacting campus safety. Meanwhile, intelligent fire detection and early warning methods have been proposed and applied in forest fire prevention and urban building fire prevention. This paper addresses the issue of campus fires by first proposing a fire detection model based on object detection algorithms, trained with fire sample data. The trained model achieved an accuracy of 94% and a recall rate of 92%. Next, executable files were created to connect campus video data with the program, facilitating intelligent and convenient campus fire early warning through the collaborative work of monitoring devices, displays, and servers. Finally, different fire prevention measures were proposed for different areas of the campus.
Source: ce/papers
DOI: 10.1002/cepa.3284
Authors: Kexue Yang, Jing Zhao, Jixian Li, Chen Xia
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4408562937