SwarmFusion: Revolutionizing Disaster Response with Swarm Intelligence and Deep Learning
June 10, 2025 ยท Declared Dead ยท ๐ arXiv.org
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Authors
Vasavi Lankipalle
arXiv ID
2507.00005
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.LG
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Disaster response requires rapid, adaptive decision-making in chaotic environments. SwarmFusion, a novel hybrid framework, integrates particle swarm optimization with convolutional neural networks to optimize real-time resource allocation and path planning. By processing live satellite, drone, and sensor data, SwarmFusion enhances situational awareness and operational efficiency in flood and wildfire scenarios. Simulations using the DisasterSim2025 dataset demonstrate up to 40 percentage faster response times and 90 percentage survivor coverage compared to baseline methods. This scalable, data-driven approach offers a transformative solution for time-critical disaster management, with potential applications across diverse crisis scenarios.
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