Tokay PRO: RISC-V Edge AI Camera
High-performance Edge Computing on RISC-V
This year’s goal is to develop a high-performance devkit using one of Canaan Kendryte’s chips based on RISC-V.
While the current devkit is optimized for ultra-low power usage, the next iteration of our devkits focuses on high performance.
We got feedback from folks at Hacker News and Hackaday , a lot of people were interested in the device that will be able to do multi-object recognition with 4k/60 fps video stream, and with the current AI accelerated video chip market being where it is right now, the Kendryte is the logical setup to use for this project for RISC-V.
The Spec We Aim For
With chips like K510, it is possible to achieve real-time detection of multiple objects (traffic counting, accident detection, object avoidance.) More importantly, this chip class is manufacturing-ready and can be used in real-life development without switching between devkit and production chips. If you want to develop something using a camera and juicy AI chip, hit us up :)
While devkits are awesome , we aim to show an actual demo project using edge computing, and we choose Inventures as our platform for May 30. We will showcase an interactive stand-alone hardware platform that helps physical businesses to remove friction in stores.
Onboard SoC | Kendryte K510, Dual Core RISC-V |
CPU Frequency | 800MHz |
Camera Interface | MIPI-CSI |
Night Vision | Yes |
Stock Camera Sensor | IMX219 |
Video Resolution | 8MP - 3840x2160 |
Raw Video Frame Rate | 30 FPS |
Video Encoding | H264 @ 30 FPS |
Available RAM | 2Gb |
Available Storage | 4Gb eMMC |
External Storage | SD Card |
Sensors | Light Sensor, Passive IR (Motion Detection) |
Connectivity | WiFi, USB-C |
Power Options | USB-C with backup battery |