Abstract: This project proposes an intelligent toll gate security system integrating machine learning and IoT-based sensors for enhanced vehicle monitoring and safety checks at toll gates. When a vehicle approaches the toll, a camera activates to capture and detect the vehicle's number plate, identifying it through image processing algorithms. Additionally, metal sensors analyses the vehicle to detect any unauthorized metallic objects, such as weapons. If any potential threat is detected, the system prevents the vehicle from passing by automatically controlling a gate mechanism powered by a DC motor connected to an ESP-32. The system also alerts higher authorities through a notification sent via a Telegram bot. In cases where police personnel allow vehicles to pass without thorough inspection, notifications are sent to higher authorities, with vehicle tracking for further monitoring. This setup uses a laptop camera as the visual input for machine learning tasks, while ESP-32 manages sensors and gate operations through UART communication. The proposed system enhances toll gate security, ensuring strict vehicle checks and real-time alerts to prevent unauthorized or hazardous vehicle entry.
Keywords: Check post Security, Unauthorized Access, Alerts, Weight detector.
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DOI:
10.17148/IJARCCE.2025.14508
