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Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures pp 139–159Cite as

Perspectives of Using Artificial Intelligence in Building Fire Safety

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Abstract

Over the past decade, big data and artificial intelligence (AI) enable new smart techniques in the building and construction area. The applications of AI in fire detection, risk assessment, and fire forecast are emerging. This chapter provides a roadmap for AI-based building fire safety engineering application by comparing it with the history of CFD fire modelling. Guidelines for constructing a reliable fire database with both experimental and numerical data are introduced. The AI algorithms having a great potential to detect and forecast fire scenarios are discussed, and the latest research on exploring and developing intelligent firefighting systems are reviewed. Finally, three new concepts of applying AI in building fire safety are proposed, (1) the AI-based fire engineering design to improve the structure fire safety, (2) the building fire Digital Twin to monitoring the fire risk and development in real time, and (3) the Super Real-time Forecast (SuRF) of the fire evolution.

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Acknowledgements

This work is funded by the Hong Kong Research Grants Council Theme-based Research Scheme (T22-505/19-N) and the PolyU Emerging Frontier Area (EFA) Scheme of RISUD (P0013879).

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Authors and Affiliations

  1. The Hong Kong Polytechnic University, Kowloon, Hong Kong

    Xinyan Huang, Xiqiang Wu & Asif Usmani

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  1. Xinyan Huang
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Correspondence to Xinyan Huang .

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  1. Clemson University, Clemson, SC, USA

    Dr. MZ Naser

  2. John Jay College of Criminal Justice, New York, USA

    Glenn Corbett

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Huang, X., Wu, X., Usmani, A. (2022). Perspectives of Using Artificial Intelligence in Building Fire Safety. In: Naser, M., Corbett, G. (eds) Handbook of Cognitive and Autonomous Systems for Fire Resilient Infrastructures. Springer, Cham. https://doi.org/10.1007/978-3-030-98685-8_6

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