EmergeSense : AI-Based Disaster Response System

🎥Video Demonstration

Click here to watch the video demonstration

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📝 Overview

EmergeSense is an AI-powered disaster response system designed to assist disaster management agencies in monitoring, detecting, and responding to natural calamities in real-time.

By integrating data from social media platforms, satellite imagery, and climate data, the system leverages AI-driven analytics to identify affected regions and generate effective, coordinated response strategies.

This project combines deep learning models, Google Earth Engine, and real-time data aggregation to provide actionable insights for disaster response teams. The system is implemented as a centralized web and mobile application for efficient data visualization and management.

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✨ Key Features

🌐 Real-time Social Media Data Integration

• Scrapes and analyzes posts from platforms like X (formerly Twitter) and Instagram.
• Uses Natural Language Processing (NLP) models to detect disaster-related posts and extract geolocation data.

🛰️ Satellite Imagery Analysis

• Utilizes Google Earth Engine for near-real-time analysis of satellite images.
• Detects flood-affected regions and visualizes changes over time using machine learning techniques.

🤖 Disaster Detection using Deep Learning

• Employs deep learning models to predict affected areas based on historical disaster patterns and real-time data.
• Custom-trained models analyze satellite and climate data for flood detection, fire outbreaks, and other disasters.
• Detailed information about our Earthquake Prediction Model can be found here.

🌦️ Real-time Climate Data

• Integrates real-time climate data from reliable weather data providers to enhance prediction accuracy.
• Analyzes climate trends to predict potential future disasters.

🗺️ Centralized Dashboard for Data Visualization

• A web and mobile application consolidates all disaster-related data.
• Interactive maps display real-time satellite imagery, social media activity, and identified disaster zones.
• Supports role-based access for stakeholders like rescue teams and government authorities.

🤝 Response Generation and Coordination

• Provides insights into the most affected areas.
• Automates the generation of response strategies based on the severity and location of disasters.

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🚑 Response Agency Application

The Response Agency Application is an extension of the EmergeSense system, designed specifically to help response agencies cater to disaster victims efficiently. It provides tools for:

• 📍 Real-time Location Tracking: Track the locations of victims and rescue teams.
• 📋 Resource Management: Manage resources like food, water, and medical supplies.
• 📊 Incident Reporting: Allow field agents to report incidents in real-time with geotagged data.
• 📡 Communication: Facilitate communication between response teams and central command.
• 📌 Volunteer Coordination: Assign tasks to volunteers and track their progress.

This application ensures that response agencies can act swiftly and effectively during disaster situations.

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🛠️ Technology Stack

Frontend:

• ⚛️ React for the web application.
• 🐦 Flutter for the mobile application.

Backend:

• 🟢 Node.js with Express for the backend server.
• 🌍 Integration with Google Earth Engine for satellite image analysis.
• 📱 API integration with social media platforms like X and Instagram.
• 🔥 Firebase for real-time database and authentication.

AI/ML:

• 🧠 Deep learning models for disaster detection using frameworks like TensorFlow or PyTorch.
• 📖 NLP models for social media data analysis using Hugging Face Transformers.

Geospatial Analysis:

• 🛰️ Google Earth Engine for satellite imagery and environmental data.
• 🗺️ Geospatial data visualization using libraries like Leaflet or Mapbox.

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🛠️ How It Works

• 📥 Data Collection:
  The system scrapes social media platforms and ingests satellite and climate data.

• 🧠 Data Processing:
  AI models analyze the incoming data for disaster detection, geolocation extraction, and climate trend analysis.

• 📊 Visualization:
  The processed data is visualized on the centralized dashboard (web and mobile apps).

• 🤝 Response Coordination:
  The system generates response strategies and provides actionable insights for disaster management teams.

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👥 Contributors

Name	GitHub Profile	LinkedIn Profile
Rishi Kokil	GitHub	LinkedIn
Ilham Syed	GitHub	LinkedIn
Pavan Thakur	GitHub	LinkedIn
Amit Murkalmath	GitHub	LinkedIn

⚙️Setup

• Navigate to the Project Directory

  cd /path/to/your/project

Installing Python Packages

1. Move to the Directory Data Analysis

   cd Data-Analysis

2. Create a Virtual Environment

   python -m venv venv

3. Activate the Virtual Environment

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

4. Install Required Libraries

   After activating the virtual environment, install the necessary dependencies:

   pip install -r requirements.txt

Starting our Website

1. Navigate to the Website Directory

   cd Frontend/EmergeSenseWebsite

2. Install all the Dependencies

   npm install

3. Start the Development Server

   npm run dev

Disclaimer

This is an ongoing project and may contain missing files or incomplete information. Please note that certain features may not function as expected, and the project may be unstable or broken in its current state.
Additionally, this is not an open-source project. Unauthorized distribution or use of the project code or components is prohibited.