INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGY TO IMPROVE  THE EFFICIENCY OF EVACUATION OF PEOPLE IN CASE OF FIRE

Melnikov Grigoriy; Tursenev Sergey

doi:doi:10.61260/2307-7476-2024-2023-4-30-36

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INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGY TO IMPROVE THE EFFICIENCY OF EVACUATION OF PEOPLE IN CASE OF FIRE

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INTEGRATION OF ARTIFICIAL INTELLIGENCE TECHNOLOGY TO IMPROVE THE EFFICIENCY OF EVACUATION OF PEOPLE IN CASE OF FIRE

Journal: NATURAL AND MAN-MADE RISKS (PHYSICO-MATHEMATICAL AND APPLIED ASPECTS) Volume 2023 № 4 , 2024

Rubrics: ENGINEERING AND INFORMATION SECURITY IN EMERGENCY SITUATIONS

UDK 614.842 Извещение о пожаре. Пожарная тревога. Техника и тактика тушения пожара. Организация тушения пожара

Melnikov Grigoriy ¹

Tursenev Sergey ²

Author and publication information

Authors:

1. Saint-Petersburg university of State fire service of EMERCOM of Russia (Department of postgraduate study, postgraduate student)

Russian Federation

2. Saint-Petersburg university of State fire service of EMERCOM of Russia (department of fire extinguishing and emergency rescue operations, head of the department)

Russian Federation

Type:

Article

DOI:

https://doi.org/10.61260/2307-7476-2024-2023-4-30-36

Pages:

from 30 to 36

Status:

Published

Received:

17.09.2023

Accepted:

19.11.2023

Published:

14.02.2024

Subject area:

UDK 614.842 Извещение о пожаре. Пожарная тревога. Техника и тактика тушения пожара. Организация тушения пожара

Language:

Russian

Keywords:

evacuation, improvement, artificial intelligence, machine learning

Abstract and keywords

Abstract (English):
The application of artificial intelligence technology to improve the evacuation control system at fires is considered. The focus is on the shortcomings of traditional evacuation methods and the potential of artificial intelligence in big data processing to optimize the flow of people. The integration of artificial intelligence algorithms with models of human behavior to develop more effective evacuation scenarios that take into account the psychological and physiological aspects of human behavior in emergency situations is discussed.

Keywords:
evacuation, improvement, artificial intelligence, machine learning

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References

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