Polling Station Monitoring System

Project Overview

This project was developed for the District Administration Jalandhar to monitor and manage rush at polling stations during elections. The system was built to handle high traffic and manage data from approximately 1.6 million users. The focus was on designing a scalable backend architecture to ensure performance and reliability.

Key Features

• Real-time Monitoring: Efficiently tracked user activities and rush at polling stations.
• High-Volume Traffic Management: Optimized to handle a load of around 1.6 million users.
• Scalable Architecture: Designed to handle increasing traffic using clustering and load balancing techniques.
• Caching: Implemented Redis for efficient data caching and faster access.
• Security: Set up firewall rules and other security measures to ensure the system's integrity.
• Load Balancing: Used Nginx for load balancing and reverse proxy to distribute traffic effectively.
• Optimized Database Interactions: Managed high-frequency read/write operations using MongoDB with bulk updates.

Technologies Used

• Backend:
  • Express.js and Node.js
• Database:
  • MongoDB
• Caching:
  • Redis
• Load Balancer:
  • Nginx
• Clustering:
  • Node.js Clustering for parallel processing

Architecture Overview

• Server: The backend was developed using Express and Node.js, ensuring fast, asynchronous handling of requests.
• Data Storage: A MongoDB database was used to store all relevant data securely.
• Caching: Redis was integrated to optimize repeated queries, reducing the load on the database.
• Load Balancer: Nginx was used as a reverse proxy, distributing traffic evenly across the Node.js cluster.
• Node.js Clustering: Enhanced the performance by utilizing multi-core CPU architecture.

System Design

The system was designed to be modular and scalable. It featured:

• Horizontal scaling using load balancing and reverse proxy
• Distributed caching to reduce database load and improve response times
• Clustering to utilize multiple processor cores and handle concurrent requests more effectively

Security Considerations

• Firewall Rules: Configured firewalls to restrict unauthorized access.
• Secure Data Handling: Ensured that data interactions were protected using best security practices.

How to Run the Project Locally

1. Clone the repository:

   git clone https://github.com/yourusername/polling-station-monitor.git

2. Install dependencies:

   cd polling-station-monitor
   npm install

3. Set up environment variables: Configure your .env file for MongoDB, Redis, and other necessary settings.
4. Start the application:

   npm run start

Future Enhancements

• Integration of real-time analytics to provide insights on polling station activities.
• Improved fault tolerance and system failover mechanisms.
• Expansion to support multi-region deployments for broader election coverage.

License

This project is licensed under the MIT License.