Evidence map›Paper›PMID 41078483›Full record

ArticleComputational urban science2025

Towards a digital twin for smart resilient cities: real-time fire and smoke tracking and prediction platform for community awareness (FireCom).

Kijin Seong, Junfeng Jiao, Ryan Hardesty Lewis, Arya Farahi, Paul Navrátil, Nate Casebeer, Braniff Davis, Justice Jones, Dev Niyogi

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational urban science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Kijin SeongUrban Information Lab, The School of Architecture, The University of Texas at Austin, Austin, TX USA.ORCID 0000-0003-3942-6984
Junfeng JiaoUrban Information Lab, The School of Architecture, The University of Texas at Austin, Austin, TX USA.ORCID 0000-0002-7272-8805
Ryan Hardesty LewisUrban Information Lab, The School of Architecture, The University of Texas at Austin, Austin, TX USA.ORCID 0009-0002-3495-8041
Arya FarahiDepartment of Statistics and Data Sciences, The University of Texas at Austin, Austin, TX USA.ORCID 0000-0003-0777-4618
Paul NavrátilTexas Advanced Computing Center, The University of Texas at Austin, Austin, TX USA.
Nate CasebeerHomeland Security Emergency Management, Austin, TX USA.
Braniff DavisAustin Fire Department, Austin, TX USA.
Justice JonesAustin Fire Department, Austin, TX USA.
Dev NiyogiDepartment of Geological Sciences, Jackson School of Geosciences, Department of Civil, Environmental and Architectural Engineering, and the Oden Institute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, TX USA.ORCID 0000-0002-1848-5080

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

3D digital twinData aggregationSmart citySmoke predictionUrban fire

Identifiers

PMID41078483
PMCPMC12513986

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.