Parking Management System with AI License Plate Recognition
Note: The image is for demonstration purposes only. It does not represent the actual software interface, and the software name is not accurate.
Project Overview
This is a comprehensive parking management software designed for residential complexes. The system utilizes AI-powered custom license plate recognition (LPR) technology to automate and secure the vehicle entry process. It validates vehicle access based on the plate number, tracks entry and exit history for security purposes, and displays detailed information about the vehicle's owner, including their residential unit address and contact number. The software is seamlessly integrated with the community's management systems, providing a unified platform for both security and operational needs.
Key Features
- Custom AI License Plate Recognition: The LPR system is built using a custom-trained model that was specifically trained on a dataset of 5,000 images, including 800 images captured within parking lots. This ensures the model performs optimally in complex environments, such as parking garages, where lighting and angles vary.
- Enhanced Plate Character Recognition: In addition to vehicle detection, a dedicated model was trained on a dataset of 20,000 images containing license plate characters (letters and numbers) to significantly improve the accuracy of plate number recognition.
- Real-Time Entry & Exit Tracking: Logs all vehicle movements for enhanced security and monitoring.
- Owner Information Display: Displays the vehicle owner's name, unit address, and contact number for quick identification.
- System Integration: Fully integrates with the complex's existing management software for streamlined operations.
- Scalable Database Support: Uses PostgreSQL for large-scale deployments, and SQLite for embedded, small-scale installations.
- User-Friendly Interface: Developed with Vue 3, providing an intuitive and responsive front-end experience.
Technology Stack
- Frontend: Vue.js 3 – A modern JavaScript framework for building dynamic and responsive user interfaces.
- Backend: NestJS – A progressive Node.js framework designed for building scalable server-side applications.
- Database: PostgreSQL – A robust relational database system ideal for handling large datasets.
- Embedded Database: SQLite – Lightweight and efficient for smaller, embedded use cases.
- AI Technology:
- License Plate Detection Model: A custom model trained on 5,000 images, including 800 from parking lot environments, to accurately detect vehicles in varied conditions.
- Plate Character Recognition Model: A dedicated model trained on 20,000 images of alphanumeric license plate characters for high-precision recognition.