What is it about?
Human life, infrastructures, and environment can all suffer greatly from disasters, whether man-made or natural. The growing prevalence of Big Data Analytics (BDA) techniques and Internet of Things (IoT) technologies as well as Artificial Intelligence (AI) methods presents significant opportunities and solutions for Emergency Management (EM) authorities. These technologies provide cutting-edge supports and foundations that enable a better understanding of events. In this paper, we review relevant existing research works dealing with EM and we propose an innovative two-level classification: the first level refers to the type of disasters and the second one represents the specific emergency situations for each level-one type. This classification serves as a systematic framework to organize and structure the current state-of-the-art in this field, in particular, it summarizes the main challenges encountered and addressed in the literature. Furthermore, the discussion and the comparison of the main literature works according to this proposed classification allowed us to easier identify key and relevant trends, issues and gaps of the existing contributions. Thus, we identified and highlighted various open issues and proposed future research directions that would be very interesting to explore and investigate in order to improve different aspects related to this important and highly concerning area.
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Why is it important?
we identify and highlight various open issues and propose future research directions that would be very interesting to explore and investigate in order to improve different aspects related to this important and highly concerning area.
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This page is a summary of: Big Data Analytics and Internet of Things Combined with Artificial Intelligence Techniques for Effective Emergency Management: A Comprehensive Survey, ACM Computing Surveys, May 2026, ACM (Association for Computing Machinery),
DOI: 10.1145/3806828.
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