REVOLUTIONIZING FIREFIGHTING TRAINING WITH DIGITAL TWINS: REAL-TIME FIRE SPREAD SIMULATION AND ESCAPE ROUTE OPTIMIZATION

The advancement of digital twin (DT) systems had revolutionized various industrial and safety applications, offering virtual replicas of physical processes for improved monitoring and training. Fire scenarios are highly dynamic, with conditions changing rapidly due to factors like wind direction, material flammability, and structural integrity. This study explored the application of a smart fire scene DT system (SFSDTS) for firefighting training and safety management. The novelty and contributions of this study was the proposed SFSDTS integrated machine learning models to predict fire spreading paths and estimate escape routes in real-time, providing an immersive and interactive training environment for firefighters.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-14
DOI
https://doi.org/10.5281/zenodo.15405690
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
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article

REVOLUTIONIZING FIREFIGHTING TRAINING WITH DIGITAL TWINS: REAL-TIME FIRE SPREAD SIMULATION AND ESCAPE ROUTE OPTIMIZATION

Zenodo (CERN European Organization for Nuclear Research)
Advanced Control Systems Optimization
article

REVOLUTIONIZING FIREFIGHTING TRAINING WITH DIGITAL TWINS: REAL-TIME FIRE SPREAD SIMULATION AND ESCAPE ROUTE OPTIMIZATION

article en

Abstract

The advancement of digital twin (DT) systems had revolutionized various industrial and safety applications, offering virtual replicas of physical processes for improved monitoring and training. Fire scenarios are highly dynamic, with conditions changing rapidly due to factors like wind direction, material flammability, and structural integrity. This study explored the application of a smart fire scene DT system (SFSDTS) for firefighting training and safety management. The novelty and contributions of this study was the proposed SFSDTS integrated machine learning models to predict fire spreading paths and estimate escape routes in real-time, providing an immersive and interactive training environment for firefighters.

Zenodo (CERN European Organization for Nuclear Research)
Kingston Technology (United States) (US), University of Nottingham Ningbo China (CN)
Affordable and clean energy
Openalex Percentile: Top 59%
Advanced Control Systems Optimization
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REVOLUTIONIZING FIREFIGHTING TRAINING WITH DIGITAL TWINS: REAL-TIME FIRE SPREAD SIMULATION AND ESCAPE ROUTE OPTIMIZATION · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS