Literature DB >> 34740667

Disruptive technologies as a solution for disaster risk management: A review.

Hafiz Suliman Munawar1, Mohammad Mojtahedi2, Ahmed W A Hammad2, Abbas Kouzani3, M A Parvez Mahmud3.   

Abstract

Integrating disruptive technologies within smart cities improves the infrastructure needed to potentially deal with disasters. This paper provides a perspective review of disruptive technologies such as the Internet of Things (IoT), image processing, artificial intelligence (AI), big data and smartphone applications which are in use and have been proposed for future improvements in disaster management of urban regions. The key focus of this paper is exploring ways in which smart cities could be established to harness the potential of disruptive technologies and improve post-disaster management. The key questions explored are a) what are the gaps or barriers to the utilization of disruptive technologies in the area of disaster management and b) How can the existing methods of disaster management be improved through the application of disruptive technologies. To respond to these questions, a novel framework based on integrated approaches based on big data analytics and AI is proposed for developing disaster management solutions using disruptive technologies.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Big data; Cloud computing; Disaster management; Internet of Things; Smart cities; Wireless communication

Mesh:

Year:  2021        PMID: 34740667     DOI: 10.1016/j.scitotenv.2021.151351

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Cloud- and Fog-Integrated Smart Grid Model for Efficient Resource Utilisation.

Authors:  Junaid Akram; Arsalan Tahir; Hafiz Suliman Munawar; Awais Akram; Abbas Z Kouzani; M A Parvez Mahmud
Journal:  Sensors (Basel)       Date:  2021-11-25       Impact factor: 3.576

2.  Automatic Target Detection from Satellite Imagery Using Machine Learning.

Authors:  Arsalan Tahir; Hafiz Suliman Munawar; Junaid Akram; Muhammad Adil; Shehryar Ali; Abbas Z Kouzani; M A Pervez Mahmud
Journal:  Sensors (Basel)       Date:  2022-02-02       Impact factor: 3.576

  2 in total

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