Applications of artificial intelligence in enhancing building fire safety

Ruchit Parekh

doi:10.30574/ijsra.2024.13.1.1781

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Applications of artificial intelligence in enhancing building fire safety

Ruchit Parekh ^*

Department of Engineering Management, Hofstra University, New York, USA.

Review Article

International Journal of Science and Research Archive, 2024, 13(01), 1117–1132.
Article DOI: 10.30574/ijsra.2024.13.1.1781
DOI url: https://doi.org/10.30574/ijsra.2024.13.1.1781

Publication history

Received on 11 August 2024; revised on 17 September 2024; accepted on 25 September 2024

Abstract

In the last ten years, the integration of big data and artificial intelligence (AI) has introduced innovative smart technologies within the building and construction sectors. AI is increasingly being applied to fire detection, risk evaluation, and fire prediction. This chapter outlines a roadmap for incorporating AI into building fire safety engineering, drawing comparisons to the evolution of Computational Fluid Dynamics (CFD) fire modeling. It offers guidelines for developing a comprehensive fire database, using both experimental and simulated data. The chapter also explores AI algorithms with significant potential for detecting and forecasting fire scenarios, and reviews recent advancements in intelligent firefighting systems. Lastly, three new concepts for utilizing AI in building fire safety are proposed:
· AI-driven fire engineering design for enhancing structural fire safety,
· the implementation of a building-fire Digital Twin for real-time fire risk and development monitoring, and
· the Super Real-time Forecast (SuRF) for predicting fire progression.

Keywords

Artificial intelligence; Building fire safety; Fire detection; Risk assessment; Fire forecasting; Computational Fluid Dynamics (CFD); Fire engineering design; Digital Twin; Intelligent firefighting; Super Real-time Forecast (SuRF)

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How to cite this article

Ruchit Parekh. Applications of artificial intelligence in enhancing building fire safety. International Journal of Science and Research Archive, 2024, 13(01), 1117–1132. https://doi.org/10.30574/ijsra.2024.13.1.1781

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