Auto Timed Smart Parking Bill Generation System

Abstract

Parking management has become a challenging task due to the increasing number of vehicles in urban areas. Traditional parking systems rely on manual monitoring and ticket-based billing, which leads to inefficiency and human errors. This paper presents an Auto Timed Smart Parking Bill Generation System using Optical Character Recognition (OCR) for vehicle license plate detection. The systems use IR sensors, ESP32 microcontroller, servo motors, webcam, and a Flask Server for automated parking management. When a vehicle arrives at the entry gate, the webcam captures the license plate and OCR technology extracts the vehicle number, which is stored along with the entry time in the server database. When the vehicles reach the first exit gate, the system recognizes the license plate again and records the exit time. The total parking duration is calculated automatically the parking bill is generated. A QR code is then displayed for payment. The system also includes a dual exit gate, mechanism to prevent tailgating ensuring secure vehicle exit. The proposed system improves parking efficiency, reduces manual work, and accurate automated billing.

Introduction

The rapid increase in vehicles in urban areas has created major parking management challenges such as traffic congestion, inefficient billing, delays, and security issues. Traditional manual parking systems rely on human supervision and ticket-based methods, which often result in errors, slow processing, and problems like tailgating, where multiple vehicles exit without paying.

To solve these problems, the proposed system introduces an Auto-Timed Smart Parking Bill Generation System that uses automation, IoT devices, and image processing. The system integrates Optical Character Recognition (OCR) for detecting vehicle license plates, infrared (IR) sensors for vehicle detection, and servo-controlled gates managed by an ESP32 microcontroller. A Flask-based web server stores vehicle data, records entry and exit times, calculates parking duration, and automatically generates parking bills.

When a vehicle arrives at the entry gate, a webcam captures the license plate image, and OCR extracts the vehicle number. The entry time and vehicle details are stored in a database. IR sensors detect the vehicle and signal the ESP32 to open the gate using servo motors. At the exit, the license plate is captured again, and the system calculates the total parking duration and generates the parking fee automatically.

A QR code containing parking details and payment information is generated, allowing users to scan it with their mobile devices to complete payment. To improve security and prevent tailgating, the system uses a dual exit gate mechanism: the first gate allows the vehicle to reach the payment area, and the second gate opens only after payment verification, ensuring only one vehicle exits at a time.

The system uses hardware components such as ESP32 microcontroller, IR sensors, servo motors, and webcams, and software tools including Python, Flask web server, and Visual Studio Code. Overall, the proposed system reduces manual effort, improves efficiency, ensures accurate billing, and enhances parking security, providing a reliable and automated parking management solution.

Conclusion

This paper presented an auto times smart parking bill generation system based on OCR- based license plate recognition and dual exit gate mechanism for anti-tailgating. The system automates vehicle identification, parking time calculation, billing generation, and payment verification. By integrating ESP32, IR sensors, servo motors, webcam, and a Flask-based backend server, the proposed system provides an efficient parking management solution. The dual exit gate mechanism enhances security by preventing unauthorized vehicle exits through tailgating. The results demonstrate that the system reduces manual effort and improves the efficiency of parking operations. Future work may focus on integrating online payment gateways and improving OCR performance under different environmental conditions.

References

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Copyright

Copyright © 2026 Dr. V. Ramesh, U. Uma, E. Harini, M. Sandhya, G. Anitha. 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.