Implementation of Smart Parking Access Control and Visitor Authentication using Raspberry Pi 4 And Machine Learning

Inefficient parking management, unauthorized vehicle access, and reliance on manual supervision remain significant challenges in urban environments. Traditional parking systems struggle with slow response times, security vulnerabilities, and inefficient space utilization. This study presents a smart parking access control and visitor authentication system using Raspberry Pi 4 and machine learning to address these issues. the system integrates a USB camera for license plate recognition, an IR sensor for vehicle detection, and a servo motor for automated gate control, managed by Raspberry Pi 4. A web-based platform facilitates real-time monitoring, ensuring enhanced security and operational efficiency. Experimental results demonstrate a 95% accuracy in vehicle detection, a 98% success rate in blocking unauthorized vehicles, and an average response time of 2.4 seconds, with temporary permit recognition processed in 3 seconds. these improvements significantly enhance security, automation, and user experience in parking management. Future research will focus on integrating additional sensors, optimizing recognition models for extreme weather conditions, and exploring AI-driven anomaly detection for enhanced security.