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. 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. Onboard 10-pin JTAG/SWD mini-header and 4-pin UART header enable the use of an external debugger and USB-serial cable.
Available accessory options include a MIPI 7-inch display, MIPI CSI camera and 5V/3A USB Type C power supply.
Highlights
Target Applications:
- Vision Accelerated Artificial Intelligence
- Edge-AI Applications
- Machine Learning
- Entry Access-Control Systems
- Inventory and Asset Monitoring
Key Features:
- 2x Arm Cortex-A55 @1.2GHz, 1x Arm Cortex-M33
- DRP-AI Accelerator, 3D GPU, H.264 Enc/Dec
- 2GB DDR4, 32 GB eMMC, microSD, 16 MB QSPI
- 1G Ethernet, Wi-Fi (802.11ac), Bluetooth 5
- USB (2x type-A, 1x OTG microUSB)
- CANFD (includes CAN transceiver)
- MIPI DSI and HDMI display interfaces
- MIPI CSI camera interface
- Audio Codec and 3.5mm stereo jack
- Raspberry Pi HAT compatible header
Kit Includes:
- RzBoard V2L Single Board Computer
- Dual-band U.FL connected ext. antenna
- Quick Start Instruction Card
Specifications
| Family: | AAG |
| Release date: | 0000-00-00 00:00:00 |
| Subtitle: | Power-efficient, Vision-AI Accelerated Development Board |
| CPU: | 2x Arm Cortex A55 1x Arm Cortex M33 |
| Chipset: | RZ/V2L |
| RAM: | 2 GB DDR4 |
| Flash: | 32 GB eMMC microSD slot 16 MB QSPI |
| USB: | 2x USB 2.0 host: 1x USB 2.0 OTG |
| Serial Interfaces: | 2x high-speed serial ports from PCH,2x UART with 2-wire hand shake + 2x UART w/o hand,2 x RS232C on 9pin Dsub |
| Bus Interfaces: | Pi HAT 40-pin |
| Display Interfaces: | MIPI DSI micro HDMI |
| Network Interface: | RJ45 1 Gbps LAN with two status LEDs |
| Audio Interface: | Stereo audio codec (Dialog DA7212) routed to audio jack |
| OS Support: | Linux |
| Power Requirement: | USB-C power adapter, 5V 2A |
| Environment: | Ambient Temperature: 0° ... 70°C (operating), -25° … 85°C (storage) Humidity: 5 … 95% (operating, non-condensing), 5 … 95% (storage, non-condensing) |
| Dimensions: | 85mm x 56mm |
| Highlights: | Target Applications Vision Accelerated Artificial Intelligence Edge-AI Applications Machine Learning <li |
| Chipset Brand: | RZ |
| Wireless Module: | Murata type 1ZM |
| Display Size [inches]: | 170 x 170 |
| Compute Standard: | SBC |
| Camera Interface: | MIPI-CSI; USB type-A |
| Chipset Sub-brand: | V2L |
| E14-forums: | https://community.element14.com/products/devtools/avnetboardscommunity/avnetboard-forums/f/rzboard |
| Product Brief: | FY23_800_RZBoard_V2L_Product_Brief_al.pdf |
| Target_Applications_1: | Vision Accelerated Artificial Intelligence |
| Target_Applications_2: | Edge-AI Applications |
| Target_Applications_3: | Machine Learning |
| Target_Applications_4: | Entry Access-Control Systems |
| Target_Applications_5: | Inventory and Asset Monitoring |
| Kit_Includes_1: | RzBoard V2L Single Board Computer |
| Kit_Includes_2: | Dual-band U.FL connected ext. antenna |
| Kit_Includes_3: | Quick Start Instruction Card |
| Key_Features_1: | 2x Arm Cortex-A55 @1.2GHz, 1x Arm Cortex-M33 |
| Key_Features_2: | DRP-AI Accelerator, 3D GPU, H.264 Enc/Dec |
| Key_Features_3: | 2GB DDR4, 32 GB eMMC, microSD, 16 MB QSPI |
| Key_Features_4: | 1G Ethernet, Wi-Fi (802.11ac), Bluetooth 5 |
| Key_Features_5: | USB (2x type-A, 1x OTG microUSB) |
| Key_Features_6: | CANFD (includes CAN transceiver) |
| Key_Features_7: | MIPI DSI and HDMI display interfaces |
| Key_Features_8: | MIPI CSI camera interface |
| Key_Features_9: | Audio Codec and 3.5mm stereo jack |
| Key_Features_10: | Raspberry Pi HAT compatible header |
| Product_Brief_Name: | FY23_800_RZBoard_V2L_Product_Brief_al.pdf |
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