Approach to prototyping a technical device for fire detection based on the principles of artificial intelligence

The aim of the study is to justify the developed prototype of a technical device that uses machine learning methods for early detection of fires in order to minimise damage and save human lives. The authors formulated a hypothesis about the expediency of expanding the frequency range within which the fire automation system detects the primary signs of fire in order to increase the efficiency of its operation. To test the hypothesis, a prototype has been developed, based on the typical structure of the existing fleet of fire automation systems, including an additional unit operating on the principles of artificial intelligence. The article describes an additional unit working on the principles of fuzzy logic and convolutional neural networks to analyse the data coming from video cameras and fire detectors in order to determine the fire in the early stages of ignition.

Authors

Institutions

Publication Details

Journal
E3S Web of Conferences
Published
2025-01-01
DOI
https://doi.org/10.1051/e3sconf/202562702016
Primary Topic
Fire dynamics and safety research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Approach to prototyping a technical device for fire detection based on the principles of artificial intelligence

Zulfiya Mirkhasilova, A.S Doronin, Andrey Andreev, Abdulmajid Abduganiev et al.
E3S Web of Conferences
Fire dynamics and safety research
article

Approach to prototyping a technical device for fire detection based on the principles of artificial intelligence

Zulfiya Mirkhasilova, A.S Doronin, Andrey Andreev, Abdulmajid Abduganiev, Begmat Norov
article en

Abstract

The aim of the study is to justify the developed prototype of a technical device that uses machine learning methods for early detection of fires in order to minimise damage and save human lives. The authors formulated a hypothesis about the expediency of expanding the frequency range within which the fire automation system detects the primary signs of fire in order to increase the efficiency of its operation. To test the hypothesis, a prototype has been developed, based on the typical structure of the existing fleet of fire automation systems, including an additional unit operating on the principles of artificial intelligence. The article describes an additional unit working on the principles of fuzzy logic and convolutional neural networks to analyse the data coming from video cameras and fire detectors in order to determine the fire in the early stages of ignition.

E3S Web of ConferencesVol. 627
Peter the Great St. Petersburg Polytechnic University (RU), Tashkent Institute of Irrigation and Agricultural Mechanization Engineers (UZ)
Openalex Percentile: Top 88%
Fire dynamics and safety research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Approach to prototyping a technical device for fire detection based on the principles of artificial intelligence — Zulfiya Mirkhasilova, A.S Doronin, et al. · E3S Web of Conferences (2025) | TGRS Research Map | TGRS