Description
Reviews
| Brand | - |
| Category | Robotics / STEM Teaching Tools / Development, Learning, Evaluation & Industrial Control Boards |
| Origin | - |
| Processor | Kendryte K210 RISC-V 64-bit Dual-Core |
| Max Frequency | 400MHz |
| RAM | 8MB SRAM (On-chip) |
| Flash Storage | 16MB SPI Flash |
| Camera Interface | DVP Interface for OV2640/OV5640 |
| AI Accelerator | KPU (Neural Network Processor) |
| Connectivity | USB Type-C, UART, I2C, SPI, I2S |
| Power Supply | 5V via USB or 3.3V LDO |
| Supported IDEs | MaixPy IDE, VS Code, PlatformIO |
| Primary Application | Face Recognition, Object Detection, IoT Vision |
Anonymous
Mar 20, 2026
Rating: 5/5
Perfect for RISC-V Beginners
This board is an excellent entry point into the world of RISC-V and edge AI. The face recognition demo worked out of the box with the provided camera module. Documentation is clear, and the community support is growing fast.
Anonymous
Mar 20, 2026
Rating: 5/5
Best Purchase for University Project
Bought this for my final year thesis on smart surveillance. The one-on-one technical guidance mentioned in the description was actually helpful when I got stuck configuring the WiFi module. Highly recommended for students.
Anonymous
Mar 19, 2026
Rating: 4/5
Great Hardware, Steep Learning Curve
The hardware capabilities are impressive for the price point. Running neural networks locally is smooth. However, if you are new to MicroPython or embedded C, expect to spend some time reading the tutorials before building custom projects.
Anonymous
Mar 17, 2026
Rating: 5/5
Exceeded Expectations
The speed of image processing is surprising for a microcontroller. I successfully deployed a custom model for detecting safety helmets on a construction site simulation. The GPIO pins are easy to access for additional sensors.
Anonymous
Mar 13, 2026
Rating: 5/5
Amazing Value for AI Projects
I used this for a small robotics project requiring object tracking. The KPU handles the inference incredibly well without needing a cloud connection. The form factor is compact and fits easily onto my robot chassis.
Anonymous
Mar 05, 2026
Rating: 4/5
Solid Board with Minor Quirks
We bought ten of these for our workshop. They perform consistently well for vision tasks. Occasionally, the MaixPy IDE disconnects, but a restart fixes it. Overall, a robust tool for teaching embedded AI concepts.
Q: Is it possible to train my own models directly on the board?
A: No, the board is designed for inference only. You should train your models on a PC or cloud server using frameworks like TensorFlow or PyTorch, convert them to the Kmodel format, and then upload them to the board.
Q: Are there example codes for connecting to AWS IoT?
A: Yes, our GitHub repository contains several examples for MQTT connectivity, including specific guides for integrating with AWS IoT Core and other major cloud platforms.
Q: What is the power consumption during active face detection?
A: During active AI inference with the camera running, the board typically consumes between 200mA to 300mA at 5V, depending on the complexity of the loaded model.
Q: Can I program this board using C++ instead of Python?
A: Absolutely. While MicroPython is popular for quick prototyping, the SDK fully supports C/C++ development using the Kendryte Standalone SDK or PlatformIO.
Q: Does this kit come with the camera module included?
A: Yes, the standard kit includes the K210 board and a compatible GC0328 or OV2640 camera module ready for face recognition demos.
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