Automated Toll Management System Using RFID and Image Processing

TL;DR

This paper presents an automated toll management system that combines RFID and image processing with CNN classification to improve toll collection efficiency, security, and user convenience by automating vehicle identification and fee deduction.

Contribution

The paper introduces an integrated system using RFID and CNN-based number plate recognition for secure, automated toll collection with real-time notifications and payments.

Findings

Reduced toll plaza congestion and delays.

Enhanced security through vehicle verification.

Successful implementation of CNN for number plate detection.

Abstract

Traveling through toll plazas is one of the primary causes of congestion, as identified in recent studies. Electronic Toll Collection (ETC) systems can mitigate this problem. This experiment focuses on enhancing the security of ETC using RFID tags and number plate verification. For number plate verification, image processing is employed, and a CNN classifier is implemented to detect vehicle registration numbers. Based on the registered number, a notification email is sent to the respective owner for toll fee payment within a specific timeframe to avoid fines. Additionally, toll fees are automatically deducted in real-time from the owner's balance. This system benefits travelers by eliminating the need to queue for toll payment, thereby reducing delays and improving convenience.