AI in Disaster Response: Real-time Predictions and Relief Management

Piyush Sahu , Suruchi Upadhyay , Anita Singh , Janki Sharma , Ashu Nayak

 Artificial Intelligence (AI), Disaster Response Systems, Real-time Predictions, Predictive Analytics, Machine Learning, Early Warning Systems, Geospatial AI (GeoAI), Satellite Imagery Analysis , Resource Allocation Optimization, Reinforcement Learning.

Artificial Intelligence (AI) is revolutionizing disaster response through real-time predictions and efficient relief management. By leveraging predictive analytics, machine learning models, and real-time data, AI enables early warning systems, dynamic evacuation planning, and optimized resource allocation. This paper explores the latest advancements in AI-driven disaster management, including damage assessment through satellite imagery, social media analysis for situational awareness, and the use of reinforcement learning for logistics optimization. The integration of AI with Internet of Things (IoT) sensors and geospatial technologies (GeoAI) has further enhanced disaster prediction capabilities, allowing emergency response teams to act swiftly and accurately. Despite these advancements, challenges remain in data quality, ethical considerations, and human-AI collaboration. This study highlights successful applications and future research directions to ensure AI continues to enhance global disaster resilience. 

Published Paper   E-Certificate

"AI in Disaster Response: Real-time Predictions and Relief Management", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 10, page no.c329-c336, October-2024, Available :https://ijnrd.org/papers/IJNRD2410244.pdf

Volume 9 Issue 10, October-2024

Pages : c329-c336

Paper Reg. ID: IJNRD_301474

Published Paper Id: IJNRD2410244

Downloads: 00026

Research Area: Science and Technology

Country: Naya Raipur , Chhattisgarh , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2410244

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2410244

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition