A Smart RFID Based Automatic Toll Booth Management System Using Artificial Intelligence (AI) and Internet of Things Technologies

This work presents a Smart RFID-based Automatic Toll Booth Management System utilizing a Hybrid ResNetSVM model and IoT technologies to automate vehicle identification, classification, and toll payment. The system integrates an Impinj Speedway R420 RFID reader for automatic vehicle detection and a hybrid ResNet-50 and SVM model for real-time vehicle classification. By deploying IoT-enabled devices, such as Raspberry Pi and ESP8266, and connecting to cloud platforms like AWS IoT, the system efficiently processes vehicle data, facilitating seamless toll transactions. The RFID system achieved an impressive detection accuracy of 98% at vehicle speeds under 80 km/h. However, at higher speeds, detection accuracy decreased to 75% at 200 km/h. The hybrid ResNetSVM model performed exceptionally well, achieving an average vehicle classification accuracy of 95.5% across different vehicle types, including cars, trucks, and buses. System throughput was tested with traffic volumes of up to 50 vehicles per minute, maintaining a transaction success rate of 95.5% under heavy traffic conditions. This system not only reduces toll booth congestion and human intervention but also provides secure and automated toll payment options, utilizing payment gateways such as Stripe, UPI, and PayPal with success rates over 99%. Overall, this smart toll management system improves efficiency and user experience through the use of advanced technologies.