Automated Smart Parking and Number Plate Recognition System

This study presents an Automated Smart Parking and Number Plate Recognition System designed to enhance parking efficiency in urban environments. The system integrates IR sensors, Arduino Uno, an LCD display, and Python-based OCR (Optical Character Recognition) to automate vehicle entry tracking and parking slot availability detection. IR sensors monitor vacant spaces, while an Arduino processes this data and updates real-time slot availability on an LCD screen. A camera captures vehicle number plates upon entry, and Python OCR extracts and registers the license plate information into a database for tracking. This reduces human intervention and ensures a faster, more efficient parking process. The proposed system is cost-effective, scalable, and adaptable, making it suitable for smart city applications. Additionally, automation in parking management helps reduce congestion, minimize waiting times, and enhance security through digital record- keeping. Future improvements may include RFID-based vehicle authentication, cloud storage for centralized parking data, and mobile application integration for a seamless user experience. By leveraging hardware- software integration, this system contributes to modernizing traditional parking infrastructure and improving urban mobility. Index terms: Automated Parking System, Smart Parking, Number Plate Recognition, Optical Character Recognition (OCR), Arduino Uno, IR Sensors, LCD Display, Python-based OCR, Vehicle Tracking, Parking Slot Detection, Smart City Infrastructure, Digital Record-Keeping, RFID Authentication, Cloud-Based Parking Management, Urban Mobility, Intelligent Transportation Systems.