LILIN announces that its AI cameras are now fully edge-processed and support custom models. Among these, the License Plate Recognition Camera stands out as the most developed and in-demand product in the market.
In the ever-evolving field of AI applications, license plate recognition stands as one of the most in-demand technologies, utilized in areas such as intelligent law enforcement, parking management, and access control. Beyond accuracy, the breadth of recognition—such as support for various vehicle plates, coverage of different countries, and the ability to handle special plates—plays a critical role when implementing these solutions.
LILIN has been a pioneer in license plate recognition for years, offering highly accurate algorithms even before the adoption of AI. With the integration of AI in recent years, LILIN has extended its capabilities to include vehicle recognition, creating a more comprehensive and versatile solution.
LILIN’s Intelligent Traffic Solutions encompass both license plate and vehicle recognition. The system can identify a wide range of plates, including those for standard vehicles, motorcycles, heavy-duty bikes, trucks, military vehicles, diplomatic vehicles, and test plates—essentially any plate issued by the local motor vehicle office. Additionally, the system supports the recognition of vehicle types, colors, and brands, covering a broad spectrum of both imported and domestic vehicles.
The recognition results can be integrated with LILIN’s proprietary behavior analysis system to trigger various events, such as red-light violations, illegal right turns commonly used in law enforcement, or access control and fee integration in parking management systems. The cameras come equipped with an internal access control list, enabling control based on time, vehicle type, or license plate, offering diverse applications. Moreover, the recognition results can be customized using LILIN’s official open-source SDK on GitHub.
All recognition, behavior analysis, and event processing tasks are handled by the camera itself, eliminating the need for additional computers, significantly reducing software and hardware setup costs. This streamlined framework also makes operations and maintenance easier.
