Application of Big Data in Disaster Rescue: Coupling Model, Technical System and Effect Evaluation

Abstract In the context of frequent natural disasters and man‐made disasters, which have caused huge losses to human society, this paper aims to explore the application of big data technology in disaster rescue to improve the rescue efficiency and effect. The research contents include the construction of coupling model, technical system and effect evaluation method of big data in disaster rescue. Through coupling demonstration and multi‐attribute utility analysis, the research found that big data technology can effectively solve the cooperation barriers in disaster rescue, reduce the cost of cross‐regional linkage, and optimize the allocation of resources. The coupling model and technical system can improve the key links such as disaster early warning, rapid response, optimal allocation of resources and disaster recovery. This paper also provides an evaluation method for measuring the disaster rescue effect supported by big data, which provides theoretical basis and practical guidance for relevant policy formulation and practical operation.

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Publication Details

Journal
ce/papers
Published
2025-03-01
DOI
https://doi.org/10.1002/cepa.3281
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
0.00

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Application of Big Data in Disaster Rescue: Coupling Model, Technical System and Effect Evaluation

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ce/papers
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Application of Big Data in Disaster Rescue: Coupling Model, Technical System and Effect Evaluation

Wei Zhan, Yanling Lu, Fengyu Wang, Qian Liu, Genli Tang, Xuelu Xu
article en

Abstract

Abstract In the context of frequent natural disasters and man‐made disasters, which have caused huge losses to human society, this paper aims to explore the application of big data technology in disaster rescue to improve the rescue efficiency and effect. The research contents include the construction of coupling model, technical system and effect evaluation method of big data in disaster rescue. Through coupling demonstration and multi‐attribute utility analysis, the research found that big data technology can effectively solve the cooperation barriers in disaster rescue, reduce the cost of cross‐regional linkage, and optimize the allocation of resources. The coupling model and technical system can improve the key links such as disaster early warning, rapid response, optimal allocation of resources and disaster recovery. This paper also provides an evaluation method for measuring the disaster rescue effect supported by big data, which provides theoretical basis and practical guidance for relevant policy formulation and practical operation.

ce/papersVol. 8(2)
Xuzhou University of Technology (CN), Chongqing University (CN), Northern University of Malaysia (MY), Xinjiang University (CN)
Government of Jiangsu Province, Qinglan Project of Jiangsu Province of China
Openalex Percentile: Top 94%
Big Data Technologies and Applications
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