Scalable Parking Management Using Cloud Infrastructure and DevOps

Abstract

This project presents a scalable parking management system built using PHP and SQL, integrated with cloud infrastructure and DevOps methodologies. The system dynamically scales to handle high traffic using cloud auto-scaling and load balancing techniques, ensuring reliable performance. By leveraging containerization, continuous integration, and monitoring tools, the project automates deployments and ensures minimal downtime. The goal is to provide an efficient and resilient solution to parking management challenges, enabling seamless user experience during peak times while maintaining system integrity and availability.

Introduction

I. INTRODUCTION

The web-based Parking Lot Management System, developed using PHP, is a versatile solution designed to enhance parking operations across various environments such as malls, offices, and public spaces. By leveraging the power of PHP, the system provides a reliable and scalable platform, addressing the limitations of traditional parking systems.

Key features include real-time space availability tracking, which allows users to quickly find available parking spots, reducing search time and alleviating congestion. The online booking and payment system streamlines the process by enabling users to reserve and pay for parking slots digitally, minimizing the need for cash transactions and reducing human errors. Additionally, detailed reporting tools provide administrators with insights into parking operations, facilitating data-driven decisions for optimizing space usage and revenue. The system’s benefits are clear: it enhances parking efficiency by optimizing space allocation, reduces operational errors through automation, and delivers a seamless user experience, boosting customer satisfaction. Furthermore, by maximizing parking space usage and minimizing errors, the system can help increase revenue for operators. This scalable and feature-rich platform is a valuable solution for organizations aiming to modernize parking management and improve overall customer experience.

II. LITERATURE SURVEY

1) Hasan Phudinawala, Omkar Malusare, Rushikesh Mahadik. Vehicle Parking Management System. International Journal of Advanced Research in Science, Communication and Technology , 2(1), 555-559. Doi:10.48175/IJARSCT-2995

In this study, Hasan and his team present a web-based solution for managing parking operations, offering features such as real-time tracking of parking availability, online booking, and integrated payment systems. These features aim to enhance parking efficiency and reduce congestion in urban environments. However, the system's operational efficiency under high traffic loads, especially during peak times, remains a significant challenge. Understanding these limitations, we propose to build upon this existing work by developing a cloud-enabled, scalable parking system, utilizing DevOps practices like auto-scaling and load balancing to dynamically manage resources. This approach will address the identified gaps in handling variable traffic loads and ensure seamless performance, making the system more resilient and adaptable to real-world demands.

2) Meng Ying, Yan Sun. Discussion on Parking Management System Based on Parking Behavior. International Conference on Urban Engineering and Management Science , 512-516. Doi: 10. 1109/ICUEMS50872.2020.00113.

This paper presents the influence of user parking behaviors on the effectiveness of parking management systems. They highlight that understanding behaviors such as parking duration and frequency is crucial for optimizing space allocation and reducing congestion in urban areas. The study advocates for a data-driven approach to parking management, emphasizing the integration of technological solutions to enhance responsiveness to real-time user demands.

Building on these findings, our project aims to address identified gaps by implementing cloud-based infrastructure and DevOps strategies, including auto-scaling and load balancing, which will enable the parking management system to dynamically adjust resources according to varying traffic conditions. This approach is intended to improve operational efficiency and adaptability, ensuring robust performance in real-world urban environments.

3) Keerthan Satya Devineni, D.Rohin Sri Kumar, K.N.V.Srinesh Chowdary, RK.Anirudh Varma, Smart Parking System, International Journal of Innovative Technology and Exploring Engineering, 9(2), Doi: 10. 35940/ijitee.B6537.129219.

In the paper, the authors present a comprehensive overview of innovative technologies aimed at enhancing parking management through automation and user-centric solutions. They discuss various components of the smart parking system, including real-time monitoring of parking availability, automated booking, and payment processing, all designed to optimize the parking experience for users while minimizing congestion. The authors emphasize the importance of integrating Internet of Things (IoT) devices to gather and analyze data related to parking patterns, thereby enabling better decision-making for both users and administrators. Recognizing the existing challenges in scalability and efficiency during peak demand times, our project aims to leverage cloud-based infrastructure and DevOps methodologies, such as auto-scaling and load balancing. This will ensure that the smart parking system can dynamically adapt to fluctuations in traffic, enhancing its reliability and performance in real-world applications.

III. METHODOLOGY

This methodology outlines the development of a scalable parking management system utilizing PHP and SQL, complemented by cloud infrastructure and DevOps practices. The following steps were undertaken:

1. System Design: The architecture was designed to accommodate dynamic user demands, focusing on scalability and reliability. The system integrates cloud services to facilitate auto-scaling and load balancing, ensuring optimal performance during peak usage times.
2. Cloud Infrastructure: The project was deployed on a cloud platform to leverage its elasticity. Services such as AWS or Azure were utilized to implement auto-scaling groups, which automatically adjust the number of running instances based on traffic loads, thereby maintaining performance and minimizing costs.
3. Development of Core Features: Key functionalities, including real-time parking availability tracking, user booking interfaces, and payment processing systems, were developed using PHP and SQL. This ensures that users can easily find, reserve, and pay for parking spaces through an intuitive web interface.
4. Containerization and CI/CD: Docker was employed to containerize the application, allowing for consistent deployment across various environments. Continuous Integration and Continuous Deployment (CI/CD) pipelines were set up to automate testing and deployment processes, ensuring that updates can be made swiftly with minimal downtime.
5. Monitoring and Logging: Monitoring tools, such as Prometheus or Grafana, were integrated to track system performance metrics and user interactions. This enables proactive identification of issues and facilitates data-driven decision-making for system improvements.
6. User Experience Enhancement: User feedback was gathered through usability testing to refine the interface and functionality of the application. This iterative process ensured that the final product meets user needs effectively.

IV. USE CASE DIAGRAM

Fig 1. Use Case Diagram

1. User Input: Users access the platform to provide vehicle details and desired parking times through a web interface.
2. Data Management: The system stores user and parking information in a structured SQL database, ensuring efficient data handling
3. Availability Check: Real-time space availability is assessed against the database, allowing for accurate parking slot allocation.
4. Booking and Payment: Users can book and pay for parking slots online, with the system updating the database to reflect the current status.
5. Reporting and Analytics: Administrators utilize a dashboard for insights into usage trends and revenue, aiding strategic decision-making.
6. Cloud Deployment: The system is hosted on a cloud platform, enhancing scalability and performance during high-traffic periods.

V. FUTURE WORK

1. Performance Optimization: Implement advanced algorithms for improved auto-scaling and resource management to enhance system efficiency during high-demand periods.
2. Feature Expansion: Introduce real-time updates and analytics for users, enabling better decision-making regarding parking options.
3. Mobile Application: Developing a mobile application to facilitate user interaction, allowing for easy booking and payment processes.
4. Collaborative Integration: Work with local authorities to integrate the system with existing municipal services, promoting data sharing and efficient parking management.

Conclusion

In conclusion, this project emphasizes the significance of an efficient parking management system backed by cloud infrastructure and DevOps practices. Our approach highlights the need for real-time resource optimization and enhanced user engagement. By developing this robust platform, we aim to improve parking operations, reduce congestion, and elevate user satisfaction, ultimately contributing to more sustainable urban environments.

References

[1] Hasan Phudinawala, Omkar Malusare, Rushikesh Mahadik. \"Vehicle Parking Management System\". International Journal of Advanced Research in Science, Communication and Technology, vol. 2, 2022, pp. 555-559. Doi:10.48175/IJARSCT-2995 [2] Meng Ying, Yan Sun. \"Discussion on Parking Management System Based on Parking Behavior\". International Conference on Urban Engineering and Management Science, 2020, pp. 512-516. Doi: 10. 1109/ICUEMS50872.2020.00113 [3] Keerthan Satya Devineni, D.Rohin Sri Kumar, K.N.V.Srinesh Chowdary, RK.Anirudh Varma, \"Smart Parking System\", International Journal of Innovative Technology and Exploring Engineering, vol. 9 , 2019, pp. 583-587, Doi: 10. 35940/ijitee.B6537.129219. [4] Kuldeep, Tanya, \"Parking Management Sysstem\", International Journal of Advanced Research in Science, Communication and Technology, vol. 8, 2020, pp. 588-591, Doi: 10.22214/ijraset.2020.5092 . [5] Amira. A. Elsonbaty, Mahmoud Shams, \"The Smart Parking Management System\", International Journal of Computer Science & Information Technology, vol. 12, 2020, pp. 55-66, Doi: 10.5121/ijcsit.2020.12405 [6] Pallavi H. P , Khushi, Chethanaa V. , \"Vehicle Parking Mangaement System\", IRE Journals, vol. 7, 2023, pp. 308-317, e-ISSN: 2456-8880. [7] Muhamed Alarbi, Abdelkareem Jaradat, Hanan Lutfiyya, Anwar Haque, \"SCOPE: Smart Cooperative Parking Environment\", IEEE Access , vol. 11, 2023. pp. 120346-120361, Doi: 10.1109/ACCESS.2023.3328233

Copyright

Copyright © 2024 Kedar Pattanshetti, 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.