IEEE_MOVE_IT-Dashboard

Emergency Response Optimization System (EROS)

Overview

EROS is a prototype tool developed as a Capstone Project in collaboration with the IEEE MOVE Global team and Texas A&M University. It enhances emergency response by predicting demand hotspots and dynamically routing response vehicles for efficient deployment during disasters.

Key Features

• Predictive Demand Analysis: Uses real-time and historical data to forecast emergency service needs, ensuring timely resource deployment.
• Dynamic Vehicle Routing: Optimizes routes for emergency vehicles, reducing response times.
• Data Integration: Integrates 100+ GB of environmental, demographic, and traffic data for enhanced situational awareness.
• GIS-Based Simulation: Analyzes community vulnerability through spatial data to aid in resource planning.
• Interactive Dashboard: Displays real-time hotspots, vehicle locations, optimized routes, and data visualizations for better coordination.

Collaborators

• Harikrishnan Raghukumar
• Sneha Mishra
• Udvab Shrivastav

Acknowledgments

Thanks to the IEEE MOVE Global team for their support in developing EROS.

The web application is available at Streamlit Web

To install and run locally :

STEP 1:

Clone the repo

git clone https://github.com/kr-hari/IEEE_MOVE_IT-Dashboard.git

STEP 2:

Go inside the project folder and run

pip install -r requirements.txt

STEP 3:

Run Streamlit app

streamlit run app.py