The Vehicle Tracking System is an advanced, real-time solution designed to enhance fleet management and vehicle monitoring capabilities. Leveraging state-of-the-art technologies like Node.js, React, Docker, Kubernetes, and Jenkins, this platform offers a seamless, scalable, and efficient way to track vehicles, analyze their routes, and ensure security and operational efficiency.
The system's architecture is meticulously designed to support scalability, reliability, and high performance. It combines a microservices approach for backend services with a dynamic and interactive frontend, ensuring a robust and user-friendly application.
The backend is powered by Express.js on a Node.js runtime, providing a lightweight yet powerful foundation for API services. It handles complex business logic, including real-time location data processing, historical tracking information storage, and user authentication and authorization.
- Express.js: Manages RESTful API requests, serving as the communication hub between the frontend and the database.
- MongoDB/PostgreSQL: Stores detailed tracking data, user profiles, and historical tracking records, ensuring data integrity and fast retrieval.
Built with React, the frontend delivers a rich, interactive user experience. Users can view real-time locations, track historical routes, and generate reports on vehicle activity.
- React: Ensures a responsive and intuitive interface, enhancing user engagement and satisfaction.
- Map Integration: Incorporates mapping services (e.g., Google Maps, Mapbox) to visualize vehicle locations and movements accurately.
- Docker: Containers encapsulate the application's environment, making deployments consistent across development, staging, and production.
- Docker Compose: Simplifies the management of application services, enabling easy local development and testing.
- Kubernetes: Automates deployment, scaling, and management, ensuring the application remains available and performant under varying loads.
- Jenkins: Facilitates continuous integration and deployment, automating the build, test, and deployment pipeline. This ensures that new features and fixes are reliably integrated and deployed to production.
- Real-Time Tracking: Monitor vehicle locations in real-time, providing immediate insights into fleet operations.
- Historical Data Analysis: Review historical routes and performance metrics to optimize operations and reduce costs.
- Alerts and Notifications: Configure alerts for specific events (e.g., geofence breaches, unusual activity), enhancing security and operational control.
- User Management: Securely manage user access and roles, ensuring that sensitive data remains protected.
- Clone the project repository.
- Install Docker and Docker Compose if not already available.
- Run
docker-compose upto start the application services. - Open the web application in a browser to access the Vehicle Tracking System.
For a detailed guide on setup, configuration, and usage, refer to the documentation within the project.
We welcome contributions to improve the Vehicle Tracking System. Please see the CONTRIBUTING.md file for guidelines on contributing to the project.
To track the buses on the campus in real time and showcase it on a web app.
Initial try can be viewed here:- https://reuben27.github.io/Vehicle-Tracking-System/Tracker.html
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The Live-location.ino file determines the corrdinates using the gsm module. It then sends the coordinates to the thinkspeak database.
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The Tracker.js file displays the map with the current location of the bus using google maps javascript api. The marker gets updated everytime a new location is read.
The Vehicle Tracking System is released under the MIT License. For more details, refer to the LICENSE.md file.