ISSN2456-3315
Impact Factor10.57
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ESTD2016
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Paper Title
Disaster Management and Prediction: An In-Depth Review of Modern Approaches
Authors
Amal Biju , M P Arjun Krishna , Aswin Biju , Roshan Varghese Sam , Tinimol Andrews
Keywords
Machine learning, Disaster, Prediction
Abstract
As natural disasters increase in both frequency and intensity, there is an urgent need for innovative solutions in disaster management and prediction. This survey examines the role of machine learning (ML), Internet of Things (IoT), edge computing, and artificial intelligence (AI) in developing proactive and responsive disaster management frameworks. ML and AI enable predictive analytics that can foresee disaster patterns and identify critical risk factors, while IoT and edge computing facilitate real-time data gathering and processing closer to the source. These technologies work together to enhance situational
awareness, improve emergency response times, and support efficient resource management during crises. By integrating these advanced technologies, disaster management systems are better equipped to anticipate, respond to, and recover from disasters, ultimately reducing impact and enhancing resilience. This survey highlights the strengths of these systems, along with challenges in data privacy, cost, and cross-platform interoperability, and calls for continued development in technology-driven solutions for global disaster resilience.
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How To Cite
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IJRTI — journal style
"Disaster Management and Prediction: An In-Depth Review of Modern Approaches", IJRTI - International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.10, Issue 1, page no.a511-a516, January-2025, Available :https://ijrti.org/papers/IJRTI2501062.pdf
APA — 7th edition
Biju, A., Krishna, M. P. A., Biju, A., Sam, R. V., & Andrews, T. (2025). Disaster Management and Prediction: An In-Depth Review of Modern Approaches. International Journal for Research Trends and Innovation, 10(1), a511-a516. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062
MLA — 9th edition
Biju, Amal, et al. "Disaster Management and Prediction: An In-Depth Review of Modern Approaches." International Journal for Research Trends and Innovation, vol. 10, no. 1, 2025, pp. a511-a516, https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062.
Chicago — 17th, bibliography
Biju, Amal, et al. "Disaster Management and Prediction: An In-Depth Review of Modern Approaches." International Journal for Research Trends and Innovation 10, no. 1 (2025): a511-a516. https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062.
Harvard — author–date
Biju, A. et al. (2025) 'Disaster Management and Prediction: An In-Depth Review of Modern Approaches', International Journal for Research Trends and Innovation, 10(1), pp. a511-a516. Available at: https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062
IEEE — numbered reference
A. Biju, M. P. A. Krishna, A. Biju, R. V. Sam and T. Andrews, "Disaster Management and Prediction: An In-Depth Review of Modern Approaches," IJRTI, vol. 10, no. 1, pp. a511-a516, Jan. 2025.
Vancouver — biomedical
Biju A, Krishna MPA, Biju A, Sam RV, Andrews T. Disaster Management and Prediction: An In-Depth Review of Modern Approaches. IJRTI. 2025 Jan;10(1):a511-a516.
AMA — 11th edition
Biju A, Krishna MPA, Biju A, Sam RV, Andrews T. Disaster Management and Prediction: An In-Depth Review of Modern Approaches. IJRTI. 2025;10(1):a511-a516. Accessed at https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062
BibTeX — Zotero, Mendeley, LaTeX
@article{IJRTI2501062,
author = {Amal Biju and M P Arjun Krishna and Aswin Biju and Roshan Varghese Sam and Tinimol Andrews},
title = {Disaster Management and Prediction: An In-Depth Review of Modern Approaches},
journal = {International Journal for Research Trends and Innovation},
volume = {10},
number = {1},
pages = {a511-a516},
year = {2025},
month = {January},
issn = {2456-3315},
url = {https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - Biju, Amal
AU - Krishna, M P Arjun
AU - Biju, Aswin
AU - Sam, Roshan Varghese
AU - Andrews, Tinimol
TI - Disaster Management and Prediction: An In-Depth Review of Modern Approaches
T2 - International Journal for Research Trends and Innovation
JA - IJRTI
VL - 10
IS - 1
PY - 2025
SN - 2456-3315
UR - https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062
SP - a511-a516
ER -
Issue
Volume 10 Issue 1,
January-2025
Pages : a511-a516
Other Publication Details
Paper Reg. ID
IJRTI_200372
Published Paper ID
IJRTI2501062
Downloads
205,598
Research Area
Computer EngineeringÂ
Country
Kottayam, Kerala, India
Published
January 2025
Published Paper PDF
https://ijrti.org/papers/IJRTI2501062.pdf
Published Paper URL
https://ijrti.org/viewpaperforall.php?paper=IJRTI2501062
About Publisher
International Journal for Research Trends and Innovation
Published by IJRTI (JW Publication)
2456-3315
ISSN
10.57
Impact Factor
2016
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Open
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Impact Factor 10.57 calculated by Google Scholar and Semantic Scholar.
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The content, data and findings in this article are based on the authors’ research and have been
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Declarations
Funding
No external funding was received for this study.
Conflict of Interest
The authors declare that they have no conflict of interest.
Acknowledgements
The authors would like to thank the reviewers and the editorial board of International Journal for Research Trends and Innovation for their careful reading and constructive comments, and all colleagues who supported the preparation of this manuscript.
