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AuthorAboualola, Mohamed
AuthorAbualsaud, Khalid
AuthorKhattab, Tamer
AuthorZorba, Nizar
AuthorHassanein, Hossam S.
Available date2024-03-26T11:56:47Z
Publication Date2023
Publication NameIEEE Access
ResourceScopus
ISSN21693536
URIhttp://dx.doi.org/10.1109/ACCESS.2023.3293035
URIhttp://hdl.handle.net/10576/53525
AbstractWithin the paradigm of smart cities, smart devices can be considered as a tool to enhance safety. Edge sensing, Internet of Things (IoT), big data, social media analytics, edge computing, and artificial intelligence are key technologies that can be applied through smart devices to create emergency-aware systems. The use of these technologies could make emergency management tasks such as visualizing, analyzing, and predicting disasters easier to perform. The aim of this paper is to conduct a review of recent activities in literature about disaster and emergency management, and showing the role of different edge technologies used in this regard, and through the different stages of dealing with a disaster situation. Special importance is given to two main technologies: Social media analytics and artificial intelligence, due to their exceptional impact on emergency situations. Social media represents a rich source of data while artificial intelligence stands out as the mechanism to deal with the huge amount of data generated by smart devices, and thus needed to tackle all sources of data, in order to predict, detect, manage information, and for authorities to respond to emergency situations. This survey is a comprehensive review for the recent literature on the related topics, providing the reader with a clear overview of the current status and classifying the papers into groups with relations among them. The structuring of the recent literature into four phases makes it easier for the reader to realize the current state of the art. For completeness, this survey ends with a section on open issues and research trends in disaster and emergency management systems.
SponsorThis work was made possible by Qatar University grant QUHI-CENG-21/22-1. The statements made herein are solely the responsibility of the authors. Open Access funding provided by the Qatar National Library.
Languageen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Subjectartificial intelligence
big data
Crowd management
deep learning
edge computing
emergency detection
event prediction
machine learning
response to emergency
social media
TitleEdge Technologies for Disaster Management: A Survey of Social Media and Artificial Intelligence Integration
TypeArticle
Pagination73782-73802
Volume Number11
dc.accessType Open Access


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