Publication Type
Journal Article
Version
publishedVersion
Publication Date
10-2025
Abstract
This paper discusses the development and application of a digital twin (DT) for urban resilience, focusing on an integrated platform for real-time fire and smoke. The proposed platform, FireCom, adapts DT concepts for the unique challenges of urban fire management, which differ significantly from regional wildfire systems. Through an exploratory case study in Austin, Texas, in the United States, this research bridges the theoretical foundations of 3D DT with their practical application in fire and smoke management. By fusing diverse data sources, ranging from air quality sensors and meteorological data to 3D urban infrastructure, FireCom supports both emergency response and public awareness through a publicly accessible dashboard. Unlike platforms developed primarily for wildland fire applications, FireCom is specifically designed to account for urban complexities such as building canyon effects on smoke dispersion and the heightened exposure risks associated with dense populations. This study contributes a scalable, replicable framework for municipalities seeking data-driven tools for proactive disaster management, with implications for broader climate resilience planning in urban areas.
Keywords
3D digital twin, Smart city, Urban fire, Smoke prediction, Data aggregation
Discipline
Computer Sciences
Research Areas
Integrative Research Areas
Publication
Computational Urban Science
Volume
5
Issue
1
First Page
1
Last Page
19
Identifier
10.1007/s43762-025-00212-x
Publisher
Springer
Citation
SEONG, Kijin; JIAO, Junfeng; LEWIS HARDESTY, Ryan; FARAHI, Arya; NAVRATIL, Paul; CASEBEER, Nate; DAVIS, Braniff; JONES, Justice; and NIYOGI, Dev.
Towards a digital twin for smart resilient cities: real-time fire and smoke tracking and prediction platform for community awareness (FireCom). (2025). Computational Urban Science. 5, (1), 1-19.
Available at: https://ink.library.smu.edu.sg/cis_research/496
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1007/s43762-025-00212-x