This project introduces a cost-effective system for real-time traffic monitoring using AI-Based Vehicle Type Detection and Monitoring System. The system utilizes IR sensors to detect vehicle movement on the road and classify different types of vehicles such as cars and bikes. When a vehicle passes through the sensing area, the sensors capture the signal and send it to the Arduino microcontroller for processing. The Arduino processes the sensor data and identifies vehicle type based on predefined logic. The system continuously monitors traffic flow and updates the vehicle count in real time. The results are displayed through the serial monitor, enabling easy observation and analysis. This solution provides an efficient method for automatic vehicle detection, reducing manual effort and improving accuracy in traffic monitoring. The mini- project focuses on the design and implementation of a sensor-based vehicle detection system, demonstrating a practical and low-cost approach for traffic analysis. The system can be further enhanced by integrating advanced AI techniques such as image processing and machine learning for improved vehicle classification and smart traffic management. This project highlights the importance of intelligent systems in modern transportation and supports the development of smart city infrastructure.

Keywords : Vehicle Detection, Traffic Monitoring, Arduino, IR Sensor, AI-Based System, Smart Traffic, Vehicle Counting.