University of Tasmania
Browse
DiasterSurvey.pdf (583.16 kB)

Cloud computing in natural hazard modeling systems: current research trends and future directions

Download (583.16 kB)
journal contribution
posted on 2023-05-20, 03:44 authored by Ujjwal K C, Saurabh GargSaurabh Garg, Hilton, J, Jagannath Aryal, Forbes-Smith, N
Every year, natural disasters cause major loss of human life, damage to infrastructure and significant economic impact on the areas involved. Geospatial Scientists aim to help in mitigating or managing such hazards by computational modeling of these complex events, while Information Communication Technology (ICT) supports the execution of various models addressing different aspects of disaster management. The execution of natural hazard models using traditional ICT foundations is not possible in a timely manner due to the complex nature of the models, the need for large-scale computational resources as well as intensive data and concurrent-access requirements. Cloud Computing can address these challenges with near-unlimited capacity for computation, storage and networking, and the ability to offer natural hazard modeling systems as end services has now become more realistic than ever. However, researchers face several challenges in adopting and utilizing Cloud Computing technologies in this area. Moreover, accessing the Cloud services during the disaster where the communication and power supply can break down, is still an open challenge. As such, this survey paper discusses these challenges, needs and existing problems to re ect the current research trends and outlines a conceptual Cloud-based solution framework for more effective natural hazards modeling and management systems using Cloud infrastructure in conjunction with other technologies such as Internet of Things(IoT) networks, fog and edge computing. We draw a clear picture of the current research state in the area and suggest further research directions for future systems.

History

Publication title

International Journal of Disaster Risk Reduction

Volume

38

Article number

101188

Number

101188

Pagination

1-23

ISSN

2212-4209

Department/School

School of Information and Communication Technology

Publisher

Elsevier BV

Place of publication

Netherlands

Rights statement

Copyright 2019 Elsevier Ltd.

Repository Status

  • Open

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

Usage metrics

    University Of Tasmania

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC