Welcome to the information hub for RZBoard V2L, an exciting AI on the edge device. RZ/V2L is capable of low-power, real-time AI inferencing thanks to its DRP-AI accelerator. This repository serves as a central hub for all resources related to RZBoard V2L.
RZBoard V2L is a power efficient, vision-AI accelerated development board in popular single board computer format with well supported expansion interfaces. This Renesas RZ/V2L processor-based platform is ideal for development of cost-efficient Vision-AI and a range of energy-efficient Edge AI applications.
More information & Specs
It’s RZ/V2L processor has two 1.2GHz Arm® Cortex®-A55 cores plus a 200MHz Cortex-M33 core, a MALI 3D GPU and Image Scaling Unit. This processor SoC further differentiates itself with an on-chip DRP-AI accelerator plus H.264 video (1920 x 1080) encode/decode function in silicon, making it ideal for implementing cost-effective embedded-vision applications.
RZBoard V2L is engineered in a compact Raspberry Pi form-factor with a versatile set of expansion interfaces, including Gigabit Ethernet, 801.11ac Wi-Fi and Bluetooth 5, two USB 2.0 host and a USB 2.0 OTG interface, MIPI DSI and CSI camera interfaces, CANFD interface, Pi-HAT compatible 40-pin expansion header and Click Shuttle expansion header.
The board supports analog audio applications via it’s audio codec and stereo headphone jack. It also pins-out five 12bit ADC inputs for interfacing with analog sensors. 5V input power is sourced via a USB-C connector and managed via a single-chip Renesas RAA215300 PMIC device.
Onboard memory includes 2GB DDR4, 32GB eMMC and 16MB QSPI flash memory, plus microSD slot for removable media.
Software enablement includes CIP Kernel based Linux BSP (maintained for 10 years+) plus reference designs that highlight efficient vision AI implementations using the DRP-AI core.
Available accessory options include a MIPI 7-inch display, MIPI CSI camera and 5V/3A USB Type C power supply.
- RZBoard Metalayer: Contains the Yocto metalayer specific to RZBoard V2L as well as building information
- AI SDK: Contains the Renesas AI SDK & many demo applications
- AI Library: API functions for leveraging AI applications that will run on Renesas RZ/V2L Board
- Trail Cam Demo: Demo of trail-cam capabilites
- AI Launch Demo: Demo of AI & IoT capabilities of RZBoard V2L
- Flashing Utility: Platform agnostic RzV2L flashing utility
- Smart Parking Demo: Smart Parking Ai RZBoard Kit -> Edge AI + Cloud enablement
| Topic | Description | Difficulty |
|---|---|---|
| Smart Parking AI with Telemetry | Learn how to build and deploy smart parking AI to RZBoard | Advanced |
| RZBuddy Dispenser Preview | See what smart dispenser implementations can look like on RZBoard | Advanced |
| AI Apps Integrating Linux with RTOS for Real Time Detection | Fast boot real-time inference at the edge by integrating Linux with RTOS on Avnet's RzBoard | Advanced |
| Train & Deploy ML Model on RzBoard with Edge-Impulse | Running embedded Machine Learning on RZBoard: Train a Machine learning Model on edge impulse and Deploy it on RzBoard as DRP-AI library | Advanced |
| Build your yocto image for RzBoard and Network boot it | Building an RZ/V2L image from an ubuntu machine | Advanced |
| Build an RzBoard Yocto Image integrated with FreeRTOS | Build your Yocto Image and integrate it with FreeRTOS on RZBoard for real time detection ML Apps | Advanced |
| Realtime PCB Defect-Detection using RZBoard V2L | Fast, high-accuracy, and power-efficient detection of PCB manufacturing faults | Intermediate |
| Run Machine Learning on RzBoard V2L | Translate an onnx model so you can easily run it on Avnet's RZBoard | Intermediate |
| DRP-AI dashboard for vision-AI processing on RZBoard V2L | Browser-based AI inference exercises using USB camera and power-efficient DRP-AI acceleration | Intermediate |
| Monitoring retail checkout lines with Renesas RZ/V2L | Counting people at different checkout lines using an Edge Impulse YOLOv5 | Intermediate |
| Product inspection with Renesas RZ/V2L and Edge Impulse | Performing quality inspection for manufactured parts using Edge Impulse | Intermediate |
| Counting inventory with Renesas RZ/V2L kit | Count and analyze different inventory products using an Edge Impulse YOLOv5 model | Intermediate |
| Build, Deploy, & Run a Qt Enabled Image on RZBoard V2L | Run QT applications on RZBoard V2L after learning how to build and deploy with open source software | Intermediate |
