Scalable Parking Management Using Cloud Infrastructure and Devops

Abstract

Parking management has become a critical issue in modern urban areas due to the increasing number of vehicles. Traditional parking methods rely heavily on manual intervention, leading to inefficiencies, congestion, and high operational costs. To address these challenges, this research proposes a cloud-based Parking Management System that integrates DevOps automation tools to ensure efficiency, scalability, and real-time monitoring.The system is developed using Flask, MySQL, HTML, CSS, and JavaScript and is hosted on AWS EC2 (Free Tier). It employs DevOps tools like Git, Jenkins, and Docker for automation and deployment. The proposed system allows users to check real-time slot availability, make bookings, and process payments online. It enhances parking efficiency by automating space allocation and reducing human intervention. By leveraging cloud infrastructure, this system ensures high availability and remote access. The CI/CD pipeline automates deployment and updates, improving reliability and reducing downtime.

Introduction

With increasing urban populations and vehicle numbers, parking management faces challenges like congestion, inefficient space use, and delays caused by manual systems. Traditional parking relies on manual ticketing and cash payments, leading to errors and poor real-time tracking of available slots.

This paper proposes a cloud-based Parking Management System leveraging cloud computing and DevOps automation to improve efficiency. The system allows users to view real-time slot availability, book spaces in advance, and make cashless payments, aiming to reduce congestion and optimize parking usage.

Methodology:

• An Agile development process with phases including requirement analysis, system design, development, testing, deployment, and maintenance.

• The system backend is built using Flask with a MySQL database, frontend using HTML/CSS/JavaScript.

• Deployment on AWS EC2 with Docker containerization.

• Use of Gunicorn as the application server and Nginx as a reverse proxy for improved performance.

• DevOps tools like Git for version control and Jenkins for automated CI/CD pipeline ensure quick, reliable deployments with rollback capability.

System Architecture and Features:

• Web-based interface for users and admins to interact with real-time booking.

• Backend handles booking logic, user management, and payments.

• Persistent data storage in MySQL.

• Automated deployments through CI/CD pipeline support continuous updates.

• The system is designed for high availability, scalability, and efficient load handling.

Results:

• Reliable real-time slot booking.

• High availability through AWS hosting with Elastic IP.

• Improved performance and load management with Nginx.

• Seamless, automated deployments via Jenkins.

• Stable database integration ensuring data persistence.

Conclusion

This project demonstrates by using CNN based approach for waste classification using image analysis. This desktop application provides simple tool for realtime waste classification.Although results are good, the model requires larger dataset and model advancement through vision transformers. These improvements will enable model to generalize better and can be deployed in real world environment.

References

[1] R. Sharma, M. Patel, and S. Singh, \"Cloud-based smart parking system using IoT and DevOps tools,\" International Journal of Computer Applications, vol. 182, no. 31, pp. 15–20, 2024. doi: 10.5120/ijca2024912893 [2] A. Gupta, R. Verma, and N. Roy, \"DevOps-based CI/CD pipeline for scalable web applications on AWS,\" IEEE Access, vol. 12, pp. 67540–67548, 2024. doi: 10.1109/ACCESS.2024.3355612 [3] P. Kulkarni, T. Deshmukh, and A. Kale, \"Development and deployment of real-time parking management using cloud computing,\" International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE) ,vol. 11, no.2, pp.390–396,2024. doi:10.15680/IJIRCCE.2024.1102065. [4] S. Mehta and K. Joshi, \"Integrating Jenkins and Docker for efficient CI/CD deployment of Python Flask applications,\" International Research Journal of Engineering and Technology (IRJET), vol. 11, no. 1, pp. 1023–1028, 2024. doi: 10.5281/zenodo.11020701. [5] L. Thomas and A. Nair, \"An efficient smart parking system using PHP and MySQL hosted on AWS,\" Journal of Emerging Technologies and Innovative Research (JETIR), vol. 10, no. 3, pp. 321–327, 2024. doi:10.6084/m9.figshare.23922123. [6] P. G. Das, A. N. Ranjan, and T. B. Kumar, \"Deep learning techniques for efficient solid waste classification,\" Waste Management, vol. 123, pp. 65-73, 2023. doi: 10.1016/j.wasman.2022.11.0

Copyright

Copyright © 2025 Kedar Pattansheetti, Vedant Pawar, Pornima Vibhute, Tejaswini Dalavi, Prof. Sheetal Kapse. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.