Interactive All-in-One Kiosk motherboard Manufacturers

TC-RK3568 Core board is a high-performance core board designed by Shenzhen Thinkcore based on the RK3568 micro processor of Rockchip. The CPU adopts a quad core 64 bit Cortex-A55, 22nm advanced technology, and the main frequency is up to 2.0GHz; Integrated ARM G52 2EE GPU, fully compatible with OpenGL ES 1.1/2.0/3.2, OpenCL 2.0, Vulkan 1.1, etc; Built in the third generation NPU RKNN developed by Rockchip Micro, the computing power is 0.8Tops, and it supports deep learning frameworks such as caffe, TensorFlow, mxnet, etc. The model can be converted with one click.

TC-RK3566 SOM Stamp hole system on module is equipped with Rockchip Quad coretex- A55 processor RK3566. It is suitable for scenarios such as smart NVR, cloud terminal, IoT gateway, industrial control, edge computing, turnstile gate, NAS and vehicle control.

Thinkcore is a leading China Rockchip RK3568 Atom Embedded Board manufacturers, suppliers and exporter.

RV1126 8MP 4K AI IP Camera Outdoor made in China can be bought with Low Price from Thinkcore Technology. If you want Pricelist and Quotation, you can ask us by leaving a message.

Buy Raspberry pi adapter board in Thinkcore company.

RK3568 Core Board, the quad-core 64-bit Cortex-A55 processor, with 22nm lithography process, has frequency up to 2.0GHz, delivering efficient and stable performance for data processing of back-end equipment. There are a variety of storage options, allowing customers to quickly implement the research and production of products. It supports up to 8GB RAM, with up to 32Bit width and frequency up to 1600MHz. It supports all-data-link ECC, making data safer and more reliable, and meeting the requirements of running large-memory products application. It is integrated with dual-core GPU, high-performance VPU and high-efficiency NPU. The GPU supports OpenGL ES3.2/2.0/1.1, Vulkan1.1. The VPU can achieve 4K 60fps H.265/H.264/VP9 video decoding and 1080P 100fps H.265/ H.264 video encoding. The NPU supports one-click switching of mainstream frameworks like Caffe/TensorFlow.