Tam, W.
, FANG, H.
and Ding, Y.
(2026),
Machine Learning Based Forecasting for Building Fires, European Society for Automatic Alarm Systems Journal, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=961171
(Accessed February 14, 2026)
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Machine Learning Based Forecasting for Building Fires
Published
Author(s)
, , Yifei Ding
Abstract
The fast-evolving conditions of rapid fire progressions demand swift and informed decision-making from firefighters. This paper presents a series of research efforts to develop artificial intelligent-driven technologies that provide real-time, actionable information during fire emergencies. By leveraging synthetic data and machine learning, these technologies aim to enhance hazard recognition, reduce firefighter risk, and improve operational effectiveness, ultimately strengthening life safety and mitigating property loss.Citation
European Society for Automatic Alarm Systems Journal
Pub Type
Journals
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Keywords
Artificial Intelligence, Smart Fire Fighting, Flashover Predictions, Model Interpretability, Recommendation System
Citation
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Created January 9, 2026, Updated February 12, 2026