Establishing effective communications in disaster affected areas and artificial intelligence based detection using social media platform

Raza, Mohsin, Awais, Muhammad, Ali, Kamran, Aslam, Nauman, Paranthaman, Vishnu Vardhan, Imran, Muhammad and Ali, Farman (2020) Establishing effective communications in disaster affected areas and artificial intelligence based detection using social media platform. Future Generation Computer Systems, 112. pp. 1057-1069. ISSN 0167-739X

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Official URL: https://doi.org/10.1016/j.future.2020.06.040

Abstract

Floods, earthquakes, storm surges and other natural disasters severely affect the communication infrastructure and thus compromise the effectiveness of communications dependent rescue and warning services. In this paper, a user centric approach is proposed to establish communications in disaster affected and communication outage areas. The proposed scheme forms ad hoc clusters to facilitate emergency communications and connect end-users/ User Equipment (UE) to the core network. A novel cluster formation with single and multi-hop communication framework is proposed. The overall throughput in the formed clusters is maximized using convex optimization. In addition, an intelligent system is designed to label different clusters and their localities into affected and non-affected areas. As a proof of concept, the labeling is achieved on flooding dataset where region specific social media information is used in proposed machine learning techniques to classify the disaster-prone areas as flooded or unflooded. The suitable results of the proposed machine learning schemes suggest its use along with proposed clustering techniques to revive communications in disaster affected areas and to classify the impact of disaster for different locations in disaster-prone areas.

Item Type: Article
Uncontrolled Keywords: Ad hoc networks, Heterogeneous networks (HetNets), Social sensors, Infrastructure less communications, Machine learning: 5G, Device to device: (d2d), Boosting classifiers
Subjects: G400 Computer Science
J900 Others in Technology
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: John Coen
Date Deposited: 09 Oct 2020 08:21
Last Modified: 12 Oct 2020 08:00
URI: http://nrl.northumbria.ac.uk/id/eprint/44459

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