Evidence map›Paper›PMID 41807557›Full record

ArticleScientific reports2026

A fire image transmission method via automatic fire alarm system data bus for remote fire verification in unattended locations: design and experiment.

Liming Li, Liwei Song, Wentao Ma

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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

3 authors.

Liming LiShenyang Fire Science and Technology Research Institute of MEM, 218-20 Wenda Road, Shenyang, 110034, P.R. China. liliming@syfri.com.cn.
Liwei SongShenyang Fire Science and Technology Research Institute of MEM, 218-20 Wenda Road, Shenyang, 110034, P.R. China.
Wentao MaShenyang Fire Science and Technology Research Institute of MEM, 218-20 Wenda Road, Shenyang, 110034, P.R. China.

Funding

General Program of the National Natural Science Foundation of China 52476131Key Science and Technology Project of Ministry of Emergency Management of China 2024EMST111106National Key Research and Development Program of China 2021YFC3001600
6 · The paper itself

Abstract

This study attempts to address the technical challenges of early fire detection and rapid remote verification in unattended locations. A fire image transmission method based on the data bus of Automatic Fire Alarm System (AFAS) is proposed. The Gaussian difference algorithm is used to extract feature parameters of background image and fire image. Difference regions are accurately identified by comparing the feature extrema of these two images. An encoding strategy is adopted to perform compression encoding only on the difference regions instead of the full fire image. This significantly reduces the transmitted data volume and improves the transmission efficiency, enabling remote transmission of fire image via the existing data bus of AFAS. Experimental results show that the remote transmission time of fire image is mainly affected by the resolution of the image acquisition module, the proportion of the difference region, and the transmission distance. By adjusting the resolution of the acquisition module and the layout position of the detector, the effective transmission distance could be extended. The proposed method requires neither modifying the wiring of the existing AFAS nor building a new dedicated image transmission line, thus offering significant application advantages.

Indexed as

Automatic fire alarm system data busFeature extractionImage transmissionRemote fire verificationUnattended locations

Identifiers

PMID41807557
PMCPMC13096505

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.