Ibrahim, Azhar Mohd, Venkat, Ibrahim, Subramanian, K.G., Khader, Ahamad Tajudin, De Wilde, Philippe (2016) Intelligent evacuation management systems: A review. ACM Transactions on Intelligent Systems and Technology, 7 (3). Article Number 36. ISSN 2157-6904. (doi:10.1145/2842630) (KAR id:58005)
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Official URL: http://dx.doi.org/10.1145/2842630 |
Abstract
Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios.
Item Type: | Article |
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DOI/Identification number: | 10.1145/2842630 |
Additional information: | cited By 1 |
Uncontrolled keywords: | Forecasting; Soft computing, Crowd disaster; Crowd managements; Emergency evacuation; Evacuation management; Evacuation modelling; Evacuation path guidelines; Evacuation systems; Soft computing approaches, Disasters |
Subjects: | Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Philippe De Wilde |
Date Deposited: | 24 Oct 2016 10:45 UTC |
Last Modified: | 05 Nov 2024 10:49 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/58005 (The current URI for this page, for reference purposes) |
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