Artificial Intelligence in Disaster Management: A Survey

Title

Artificial Intelligence in Disaster Management: A Survey

Creator

Arora S.; Kumar S.; Kumar S.

Description

This paper provides a literature review of cutting-edge artificial intelligence-based methods for disaster management. Most governments are worried about disasters, which, in general, are unbelievable events. Researchers tried to deploy numerous artificial intelligence (AI)-based approaches to eliminate disaster management at different stages. Machine learning (ML) and deep learning (DL) algorithms can manage large and complex datasets emerging intrinsically in disaster management circumstances and are incredibly well suited for crucial tasks such as identifying essential features and classification. The study of existing literature in this paper is related to disaster management, and further, it collects recent development in nature-inspired algorithms (NIA) and their applications in disaster management. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Source

Lecture Notes in Networks and Systems, Vol-552, pp. 793-805.

Date

2023-01-01

Publisher

Springer Science and Business Media Deutschland GmbH

Subject

Disaster management; Disaster mitigation; Disaster preparedness; Disaster recovery; Disaster response; Machine learning

Coverage

Arora S., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Kumar S., Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India

Rights

Restricted Access

Relation

ISSN: 23673370; ISBN: 978-981196633-0

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1007/978-981-19-6634-7_56

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149974082&doi=10.1007%2f978-981-19-6634-7_56&partnerID=40&md5=586c99be7c9aa9c5349f59fb3e46bbbf