Smart Response: Leveraging AI Analytics for Enhanced Disaster Resilience

The emergence of artificial intelligence and cloud computing has transformed modern disaster response capabilities, particularly by developing sophisticated real-time analytics systems for natural disaster management. This article examines the integration of AI-powered analytics platforms that synthesize data from multiple sources, including satellite imagery, meteorological stations, and social media streams, to enable rapid response during crises. This article demonstrates that cloud-based real-time analytics substantially enhance early warning systems and optimize resource allocation during disaster events while significantly improving response times compared to traditional methods. However, these technological advances raise important ethical considerations regarding data privacy and equity in access to digital resources. The findings suggest that AI-driven disaster response systems offer unprecedented capabilities in protecting communities. However, their implementation must be guided by robust frameworks that ensure equitable access and maintain privacy standards while maximizing public safety benefits.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-12-01
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.32137
Citations
1
Primary Topic
Disaster Management and Resilience
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smart Response: Leveraging AI Analytics for Enhanced Disaster Resilience

Shashank Reddy Beeravelly -
1 citations
International Journal For Multidisciplinary Research
Disaster Management and Resilience
1.13
article

Smart Response: Leveraging AI Analytics for Enhanced Disaster Resilience

Shashank Reddy Beeravelly -
article en
1 citations

Abstract

The emergence of artificial intelligence and cloud computing has transformed modern disaster response capabilities, particularly by developing sophisticated real-time analytics systems for natural disaster management. This article examines the integration of AI-powered analytics platforms that synthesize data from multiple sources, including satellite imagery, meteorological stations, and social media streams, to enable rapid response during crises. This article demonstrates that cloud-based real-time analytics substantially enhance early warning systems and optimize resource allocation during disaster events while significantly improving response times compared to traditional methods. However, these technological advances raise important ethical considerations regarding data privacy and equity in access to digital resources. The findings suggest that AI-driven disaster response systems offer unprecedented capabilities in protecting communities. However, their implementation must be guided by robust frameworks that ensure equitable access and maintain privacy standards while maximizing public safety benefits.

International Journal For Multidisciplinary ResearchVol. 6(6)
Climate action
Openalex Percentile: Top 15%
Disaster Management and Resilience
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.