emergency-optimizer

• main page
• drone page
• offline page
• prediction page

• routes page

• github link

• Ppt explain

Emergency Supply Optimizer 🚑🇮🇳

Table of Contents

• Problem Statement
• Our Solution
• Key Features
• Technology Stack
• System Architecture
• Installation Guide
• Usage
• API Documentation
• Performance Metrics
• Case Studies
• Future Roadmap
• Team
• License

Problem Statement

• 40M+ flood-affected Indians annually
• 6+ hour average relief delay
• 30% supply wastage due to poor allocation
• Internet outages disrupt coordination

Our Solution

| Feature | Impact | |———|——–| | Offline routing | 40% faster response | | Bilingual UI | 2x wider adoption | | Lightweight ML | 89% prediction accuracy |

Key Features

1. Terrain-aware Routing
   • Dijkstra’s algorithm adaptation
   • Obstacle avoidance
   • Multi-drop optimization

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1. Demand Prediction
   • Time-series analysis
   • Population density mapping

• 

1. Offline Operation
   • CSV data storage
   • SMS fallback

• 

Technology Stack

Frontend:

• HTML5, Bootstrap, jQuery
• Leaflet.js

Backend:

• Python Flask
• Pandas, Sklearn

Data:

• Google Sheets API
• Offline CSV

System Architecture

mermaid graph TD A[Field Data] –> B{Processor} B –> C[Prediction Model] B –> D[Route DB] C –> E[Allocator] D –> F[Optimizer] E –> G[Drone Control]

Installation Guide

git clone https://github.com/your-repo/emergency-optimizer.git
cd emergency-optimizer
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python app.py

Team

**VAIBHAV BABELE**
**ANUPRIYA YADAV**
**VANSH GUPTA**
**SHIVAM KUMAR**

some imaages

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