Build a smart parking lot system with automated camera-based license plate recognition and barrier arm control.
Let drivers find, reserve, and pay for parking through a mobile app using WeChat Pay or Alipay.
Manage a parking facility's fee calculation, payment processing, and real-time space availability from a Vue admin panel.
Use as a comprehensive learning resource for Java microservices architecture with Spring Cloud Alibaba, Dubbo, and Netty.
Requires a server with at least 8 CPU cores and 16GB RAM, all documentation and code comments are in Chinese.
This is a Chinese-language smart parking lot management system with integrated electric vehicle charging station support. The project is written entirely in Java on the backend and is designed to handle the full lifecycle of a parking facility: recording vehicle entries and exits via camera-based license plate recognition, calculating fees, processing payments, and sending commands to raise the barrier arm when payment clears. All content in the repository, including the README, is in Chinese. Drivers interact through a mobile app, where they can search for nearby parking lots, see available spaces and pricing, reserve a spot in advance, view their parking history, and pay from their phone without visiting a cashier. Payment options include WeChat Pay, Alipay, and bank card interfaces. After payment, the exit barrier lifts automatically within the free exit window. Parking lot operators manage everything through a separate admin web panel built with Vue. The backend uses Spring Cloud Alibaba for microservices, Spring Boot, the Dubbo service framework, and OAuth2 for authentication. Data is stored across MySQL for important records, MongoDB for less critical content like chat messages and notifications, and Redis for caching. Real-time communication between the server and hardware uses Netty4, a Java networking framework. Both Android and iOS apps are native builds. The author notes they spent three years of personal time building this after observing that existing parking systems in China were outdated and fragmented. The code is fully open source with no private dependencies included. The README is directed at developers who want to use it as a learning resource or starting point for their own parking system, and recommends a minimum server specification of 8 cores and 16GB of RAM for deployment. Active development has moved to a Gitee repository, and the GitHub copy may not receive further updates.
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