AI-Enabled Metro Access System Using ESP32 for Monitoring and MultiLayered Passenger Authentication

Abstract

In metro stations, railway terminals, airports, and high-density public transit hubs, there is a critical requirement for systems that can provide fast, secure, and automated passenger authentication while minimizing congestion and preventing unauthorized access. These environments demand multilayered verification, real-time monitoring, and efficient gate control mechanisms to ensure smooth passenger flow and enhanced security. Traditional ticketing and access systems rely on manual verification or basic card-based entry, which are prone to misuse, duplication, long queues, and lack of real-time monitoring. Furthermore, conventional systems do not integrate biometric authentication or intelligent surveillance, reducing their effectiveness in handling modern transportation challenges. To address these limitations, the proposed smart metro access system utilizes the ESP32 microcontroller to develop an intelligent and automated access control solution. The system integrates RFID-based smart card identification, fingerprint biometric authentication, and an ESP32-CAM for real-time image capture and monitoring, ensuring multi-factor authentication. Upon successful verification, a servo motor controls the gate to allow entry, while an LCD display provides passenger information and system status. Unauthorized attempts trigger buzzer alerts, enhancing security. IoT integration enables remote monitoring, centralized data management, and analytics for metro authorities. This smart system improves passenger flow efficiency, enhances security, reduces waiting time, and supports the development of intelligent and connected urban transportation systems.