Research on fire and smoke control in urban and underground confined spaces: Advances, challenges, and prospects

Abstract

The rapid economic growth and urbanization, in China have led to a substantial expansion of urban and under-ground confined spaces, consequently heightening fire risks. Efficient and environmentally sustainable fire and smoke control in these environments presents significant challenges to public safety and the stable, sustainable extraction of mineral resources. This paper provides a systematic review and summary of three key aspects: the behavioral characteristics of fire smoke in urban and underground confined spaces, technologies for fire detec-tion and early warning, and smoke control techniques. It aims to offer a rational reference for advancing fire emergency prevention and control strategies in China’s urban and underground confined spaces. By addressing the complex interactions between internal and external factors that influence fire smoke behavior in these envi-ronments, this study highlights persistent issues such as monitoring blind spots and false alarms caused by sensor drift. To tackle these challenges, the following key directions are proposed: (1) Developing multi-scale coupled models to deepen research on smoke behavior characteristics in complex environments;(2) Establishing an un-manned, precision early warning and inspection platform based on intelligent sensing and rapid response systems; (3) Creating an intelligent evacuation system utilizing virtual reality (VR), Internet of Things (IoT), and smart sensing technologies; (4) Advancing integrated fire and smoke synchronization control technology to enhance fire prevention and control capabilities in urban and underground confined spaces.

Keywords

Urban and underground confined spaces / Fire and smoke / Multi-scale coupled model / Intelligent sensing / Fire-smoke synchronization control

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Yifan Gao: Writing -review & editing, Methodology, Formal analy-sis, Conceptualization. Zuwen Liu: Writing -original draft, Resources, Investigation. Zhiguo Guo: Writing -review & editing, Resources, Methodology, Funding acquisition. Qing Wang: Writing -original draft, Methodology, Data curation. Yuji Ye: Writing -original draft, Method-ology, Data curation.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 52564022), the Jiangxi Provincial Graduate Inno-vation Special Fund Project (Grant No. YC2024-S532) and the Jiangxi Provincial College Student Innovation Training Program Project (Grant No. S202510407076).

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