Utilizing Deep Learning Technologies for Surveillance and Evaluation of Natural Anthropogenic Catastrophes: A Comprehensive Meta-Analysis

Abstract

Disaster management is the managerial function of dealing with material, human, environmental, or economic impacts of disaster. It is the process to prepare, address, and learn from the impact of huge failures. Disasters can be caused by natural and manmade reasons. Disasters pose catastrophic and significant socioeconomic impacts along with human losses and economic failures. Recent advancements in the Deep Learning and the Machine Learning have been used to deal with catastrophic and severe effects of disasters. This study is focused on recent ML and DL approaches used in disaster monitoring and the assessment by various researchers and studies published since 2010 to present. Studies published in the areas of hazard assessment, catastrophe control, hazard prediction, calamity monitoring, and other measures have been focused. Furthermore, this study examines some of the most recently created ML and DL disaster management systems. This study also provides the future research directions to conclude findings.