Research Intelligent Fire Evacuation System Based on Ant Colony Algorithm and MapX

Yang, Jing; Shi, Mingquan; Han, Zhenfeng

doi:10.1109/iscid.2014.35

Cited by 11 publications

(2 citation statements)

References 3 publications

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“…As such situation forces human beings to take split seconds decisions. The number of causalities increases exponentially in lack of proper evacuation planning In 2014 a report was submitted by National Crime Records Bureau Of India [4] which stated that out of a total 20,201 deaths occurred due to natural caused and 6.36.509 deaths occurred due to un-natural causes.The "un-natural causes" are defined as accidents that result due to human negligencesuch as electrocution, traffic accidents, fire accidents etc. The statistics are alarming therefore government has declared evacuation planning as compulsory.…”

Section: Introductionmentioning

confidence: 99%

Evacuation Plans and Simulations for Crowd Egress – A Review

Goyal¹,

Saxena²

2018

IJAEMS

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Due to growing population density and increasing complexity and congestion of human habitat evacuation planning is essential to avoid major loss of life during a natural or un-natural disaster. The paper provides a review of existing evacuation systems and strategies and also points out the possible research directions. Intelligent Evacuation Management System coupled with evolutionary and machine learning techniques such as PSO,ACO , k -mean clustering is a promising solution to ensure safe and jostle free egress of people. .

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Section: Introductionmentioning

confidence: 99%

Evacuation Plans and Simulations for Crowd Egress – A Review

Goyal¹,

Saxena²

2018

IJAEMS

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“…, is evacuation analysis , i.e., in case of disaster (fire, earthquake, etc.) [7] [1]. unfortunately, decision makers are not supported by the complex view of hazards and the various potential exits routes.…”

Section: Introductionmentioning

confidence: 99%

Fire Evacuation using Ant Colony Optimization Algorithm

Singhal¹,

Sahu²

2016

IJCA

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ACO is one of all-powerful meta-heuristics algorithms and some researchers have expressed the strength of some applications with the algorithm the evacuation route planning is the key aspect in case of fire disaster.Ant Colony Optimization (ACO) can be used in rescue planning. Altered ACO applied as the algorithm to demonstrate the potential path during emergency rescue. Physical interference during building rescue such as blockage or disaster complication has been studied in transitional probability rule of ACO.There exits multiple route from source of fire to the exit, hence the selection of shortest path is the fundamental objective of evacuation route planning.The objective of the algorithm is to minimizes the entire rescue time of all evacuees.The ant colony optimization algorithm is used to solve the complications of shortest route planning. Presented paper gives a comparative overview of various emergency scenarios using ant colony optimization algorithm.

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ICT in disaster management context: a descriptive and critical review

Kaur

Sood

2022

Environ Sci Pollut Res

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Research Intelligent Fire Evacuation System Based on Ant Colony Algorithm and MapX

Cited by 11 publications

References 3 publications

Evacuation Plans and Simulations for Crowd Egress – A Review

Evacuation Plans and Simulations for Crowd Egress – A Review

Fire Evacuation using Ant Colony Optimization Algorithm

ICT in disaster management context: a descriptive and critical review

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