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Fanless Embedded Box PC With NVIDIA Jetson Nano Supports CAN Bus Interface
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AAEON introduced its Boxer-8222AI, an embedded PC designed for AI (Artificial Intelligence) edge computing applications that features one CAN Bus interface.
The device integrates the NVIDIA Jetson Nano SoC (System on Chip). It utilizes the quad-core ARM Cortex-A57 MPCore processor, which allows processing speeds up to 472 Giga-Flops. The system is capable of operating multiple neural networks or processing several high-resolution images simultaneously. The PC also features an onboard 4-GiB RAM and a micro-SD card slot supporting 32 GiB of storage.
Further interfaces include a CAN Bus interface, four USB 3.2 ports, an EIA-232 port, LAN, and HDMI ports. Furthermore, it features a 40-pin I/O connector for sensors and controllers. A wifi expansion slot and two antenna ports are available. The integrated PoE PD (Power over Ethernet Powered Device) LAN port enables deployment without dedicated power supply when connected to a PSE gateway (Power Supply Equipment). The device utilizes the 802.3at standard, supporting a power input of 25.6 W to power the system and connected devices such as USB cameras and sensors.
The wall-mountable PC operates in rugged environments at temperatures from -10 °C to +70 °C without losing performance. Its small size also makes it suitable for deployment in tight spaces. A power supply of 12 VDC to 24 VDC is possible. Linux 4.9 (or above) is the supported operating system.
Features
- NVIDIA Jetson Nano
- PoE/PD x 1
- 4GB LPDDR4 + 32GB SD card slot
- USB 3.2 Gen 1 x 4
- M.2 E-key slot x 1 for WiFi function expansion
- DC 12 ~ 24V wide voltage power input
- Wide working temperature -10°C ~ 70°C
IoT Projects with NVIDIA Jetson Nano: AI-Enabled Internet of Things Projects for Beginners
Investigate the NVIDIA Jetson Nano capabilities, an IoT device designed to perform computations like a desktop computer. This book demonstrates how to build projects, optimize devices, programs, and daily activities with Jetson Nano's AI computation abilities.
This board consists of CPU Quad-core ARM A57 @ 1.43 GHz and GPU 128-core Maxwell. With this hardware specification, the board can run multiple neural networks in parallel for complex AI applications. With the integrated sensor and actuators, this board enables more robust IoT solutions and provides more advanced capabilities.
With this book, the reader discovers how to develop complex IoT projects with the Jetson Nano.