ResQRoute is an intelligent, web-based disaster response system designed to assist in emergency preparedness and rapid decision-making during natural disasters in India. The platform integrates user input (disaster type and location) with simulated AI-driven logic to generate real-time evacuation strategies, risk assessments, and multilingual emergency alerts.
The system aims to demonstrate how modern technologies such as Artificial Intelligence, real-time data processing, and intuitive user interfaces can be leveraged to improve disaster response efficiency and public safety.
Demo Link:
https://resqroute-wizf.onrender.com
- To design a responsive and user-friendly disaster response interface
- To simulate AI-based risk analysis for different disaster scenarios
- To provide structured evacuation guidance and emergency resource information
- To support multilingual alert dissemination (English & Hindi)
- To demonstrate a scalable framework that can integrate real-time APIs in the future
- Built using HTML, CSS, and JavaScript
- Provides an interactive UI for user input and result visualization
- Handles dynamic rendering of:
- Risk level indicators
- Evacuation steps
- Resource lists
- Emergency alerts
- Developed using Node.js with Express.js
- Handles API requests from the frontend
- Processes disaster type and location inputs
- Generates structured response data (risk level, actions, alerts)
-
The user selects:
- Disaster type (Flood, Cyclone, Earthquake, etc.)
- Target location (city or region)
-
The frontend sends a POST request to the backend (/analyze endpoint)
-
The backend:
- Interprets the disaster type
- Applies predefined logic to determine risk level
- Generates a structured emergency response
-
The response includes:
- Risk level classification (Low, Medium, High, Critical)
- Risk summary
- Evacuation instructions
- Nearby resource suggestions
- Emergency alerts in English and Hindi
-
The frontend dynamically displays results with visual indicators and structured UI components
Intelligent Risk Classification
- Assigns risk levels based on disaster type
- Uses categorized logic for realistic simulation
Evacuation Planning
- Provides step-by-step safety instructions
- Structured for clarity and quick decision-making
Resource Identification
- Suggests nearby emergency support facilities
- Includes hospitals, relief camps, and authorities
Multilingual Alerts
- Generates alerts in:
- English
- Hindi
- Ensures accessibility across diverse populations
Real-Time Simulation
- Fast response generation (< 2 seconds)
- Mimics real-world emergency systems
This system uses rule-based logic to simulate AI behavior.
It does not currently integrate live disaster data.
However, it is designed to be easily extendable with real-time APIs such as:
- IMD (Indian Meteorological Department)
- NDMA (National Disaster Management Authority)
- INCOIS (Indian National Centre for Ocean Information Services)
This makes the platform a strong foundation for future real-world deployment.
The UI is designed with a modern, futuristic theme inspired by:
- Satellite monitoring systems
- Command center dashboards
- Real-time data visualization panels
- Live status indicators
- Animated loading sequences
- Risk visualization bars
- Structured result cards
- Render (Cloud Platform) → Hosting backend and frontend
- GitHub → Version control and project management
- Does not use real-time disaster data
- Risk analysis is based on predefined logic
- Resource locations are simulated
- No integration with live GPS or mapping APIs
- Integration with real-time APIs (IMD, NDMA)
- Live satellite data processing
- GPS-based evacuation routing
- Interactive map visualization
- SMS and mobile alert system
- Machine learning-based prediction models
ResQRoute demonstrates how a combination of modern web technologies and AI-inspired logic can be used to build an efficient disaster response system. While currently operating as a simulation, the platform provides a strong conceptual and technical foundation for developing real-world emergency management solutions.