Proceedings of the International Conference on Smart Health and Intelligent Technologies (ICSHit-2024)

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AI to the Rescue: Revolutionizing Post-Disaster Recovery Systems

Authors
Rupali Vyas1, *, Vivek Agrawal2, Diksha Rani Verma2, Prakriti Patel2
1Assistant Professor Department of Computer Science Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, CG, India
2Department of Computer Science Engineering, Department of Computer Science Engineering, SSIPMT, Raipur, CG, India
*Corresponding author. Email: rupalivyas1996@gmail.com
Corresponding Author
Rupali Vyas
Available Online 30 April 2025.
DOI
10.2991/978-94-6463-704-5_18How to use a DOI?
Keywords
Disaster Management; Artificial Intelligence; Geospatial Information Systems; Real-Time Data; Emergency Response
Abstract

The increasing occurrence of natural and man-made disasters requires efficient and integrated disaster management systems. This paper reviews recent advancements in Post-Disaster Management Systems (PDMS) with a focus on preparedness, response, and recovery. By leveraging artificial intelligence (AI) and machine learning (ML), PDMS enhances predictive analysis, resource allocation, and communication, enabling communities to better manage disaster impacts. This study assesses current frameworks and makes recommendations for improvement in disaster management and response using a qualitative methodology that encompasses a comprehensive literature review and case analysis. Some of the most significant findings call attention to preparedness efforts, technology-driven solutions, and coordinated actions to reduce the adverse impacts of disasters. AI-enabled systems such as predictive analytics, automated responses, and learning considerably enhance service recovery and resilience. The research emphasizes capacity-strengthening measures, enhanced communication strategies, and the incorporation of innovative technologies to facilitate effective disaster management. Improving current gaps in the systems, this study brings community resilience while minimizing disaster-related losses through improved disaster preparedness and response strategies.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Smart Health and Intelligent Technologies (ICSHit-2024)
Series
Advances in Intelligent Systems Research
Publication Date
30 April 2025
ISBN
978-94-6463-704-5
ISSN
1951-6851
DOI
10.2991/978-94-6463-704-5_18How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Rupali Vyas
AU  - Vivek Agrawal
AU  - Diksha Rani Verma
AU  - Prakriti Patel
PY  - 2025
DA  - 2025/04/30
TI  - AI to the Rescue: Revolutionizing Post-Disaster Recovery Systems
BT  - Proceedings of the International Conference on Smart Health and Intelligent Technologies (ICSHit-2024)
PB  - Atlantis Press
SP  - 235
EP  - 245
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-704-5_18
DO  - 10.2991/978-94-6463-704-5_18
ID  - Vyas2025
ER  -