International Journal For Multidisciplinary Research

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DAVI Vision: Human Detection and Aid Allocation in Flood Disaster

Author(s) Mr. Irfan Ajmer Pasha Shaikh, Mr. Utkarsh Rajendra Pingale, Mr. Atharva Namdev Nawale, Mr. Ganesh Hari Wani
Country India
Abstract Flood disasters continue to be one of the most severe global challenges, causing widespread human displacement and infrastructural loss. While artificial intelligence and hydrological modeling have improved flood prediction accuracy, a major operational gap remains between prediction and actionable relief. Most existing systems excel at forecasting inundation patterns but fail to identify stranded individuals or generate optimized rescue and aid distribution strategies in real time. This paper introduces DAVI Vision, an end-to-end AI-driven Detection-to-Action frame- work designed to transform flood response from passive prediction to active intervention. The proposed system integrates three synergistic modules. The first, a Human Detection Module, uses drone and satellite imagery combined with deep learning techniques such as YOLO-based architectures for identifying stranded individuals, clusters, and critical zones. The second, an AI-based Aid Allocation Engine, employs optimization methods using Linear Programming and OR-Tools to distribute limited relief resources—such as medical kits, food packets, and rescue boats—based on urgency, accessibility, and demo- graphic vulnerability. The third component, a RAG + LLM Explainability Layer, fuses real-time retrieval of environmental and logistical data with Large Language Models to generate transparent, adaptive, and explainable allocation plans for field operators.
Keywords Flood Disaster Management, Artificial Intelligence, Human Detection, Drone Imagery, YOLO Object Detection, Resource Optimization, OR-Tools, Linear Programming, Explainable AI, Retrieval-Augmented Generation, Large Language Models, Decision Support Systems, Humanitarian Aid Allocation
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-13
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60500
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