Visual-Driven Inspection for Collecting the Status of Fire Safety Equipment Status in Building Spaces

Installed fire safety equipment within buildings plays a crucial role in ensuring the safety of personnel and minimizing losses. Nevertheless, if not maintained appropriately, these devices may fail to function optimally in emergency situations. As building sizes continue to grow, traditional manual inspection methods encounter significant challenges, including a heavy workload and complex information recording tasks. To tackle these issues, advanced emergency equipment detection frameworks and improvement plans have been put forward. This framework is specifically designed to overcome the problem of remote inspection being unable to accurately locate objects by establishing spatial relationships among devices, cameras, and trajectories. Firstly, the improved detection algorithm is utilized to detect objects of interest. Subsequently, these objects are located through a tracking algorithm and Visual Simultaneous Localization and Mapping (vSLAM). The on-site experimental results clearly show that the framework can effectively solve various types of equipment detection problems in a wide range of complex scenarios and holds great promise for replacing manual labor.

Authors

Publication Details

Journal
Kalpa publications in computing
Published
2025-08-28
DOI
https://doi.org/10.29007/xb79
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Visual-Driven Inspection for Collecting the Status of Fire Safety Equipment Status in Building Spaces

Jack C.P. Cheng, Xiao Zhang, Boyu Wang, Fangzhou Lin et al.
Kalpa publications in computing
Video Surveillance and Tracking Methods
article

Visual-Driven Inspection for Collecting the Status of Fire Safety Equipment Status in Building Spaces

Jack C.P. Cheng, Xiao Zhang, Boyu Wang, Fangzhou Lin, Zhengyi Chen
article en

Abstract

Installed fire safety equipment within buildings plays a crucial role in ensuring the safety of personnel and minimizing losses. Nevertheless, if not maintained appropriately, these devices may fail to function optimally in emergency situations. As building sizes continue to grow, traditional manual inspection methods encounter significant challenges, including a heavy workload and complex information recording tasks. To tackle these issues, advanced emergency equipment detection frameworks and improvement plans have been put forward. This framework is specifically designed to overcome the problem of remote inspection being unable to accurately locate objects by establishing spatial relationships among devices, cameras, and trajectories. Firstly, the improved detection algorithm is utilized to detect objects of interest. Subsequently, these objects are located through a tracking algorithm and Visual Simultaneous Localization and Mapping (vSLAM). The on-site experimental results clearly show that the framework can effectively solve various types of equipment detection problems in a wide range of complex scenarios and holds great promise for replacing manual labor.

Kalpa publications in computingVol. 22
Openalex Percentile: Top 78%
Video Surveillance and Tracking Methods
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