Name: reComputer J2021-Edge AI Device with Jetson Xavier NX 8GB module
SKU: 224343

reComputer J2021 is a powerful and compact intelligent edge box to bring up to 21TOPS modern AI performance to the edge. The full system includes the same form factor carrier board as the Jetson NX Developer Kit, one Jetson Xavier NX production module, a heatsink, and a power adapter. reComputer J2021 is preinstalled with Jetpack 4.6.1, simplifies development, and fit for deployment for edge AI solution providers working in video analytics, object detection, natural language processing, medical imaging, and robotics across industries of smart cities, security, industrial automation, smart factories.

Features

Hand-size edge AI device: built with Jetson Xavier NX 8GB Production Module, delivering 384 NVIDIA CUDA® cores delivers up to 21 TOPS AI performance with the small form factor of 130mm x120mm x 50mm.
NVIDIA Jetson Xavier NX Dev Kit alternative: the carrier board brings rich IOs including Gigabit Ethernet port, 4 USB 3.1 ports, HDMI port, and DP port
Pre-installed NVIDIA JetPack: support entire and various for building fast and robust AI application provided by Seeed Edge AI partners, helps develop innovative AI solution for manufacturing, logistics, retail, service, agriculture, smart city, healthcare, and life sciences, etc
Power-efficient: as little as 10 watts, delivering high performance, accurate, multi-modal AI inference at the edge.
Expandable with the onboard interfaces and reComputer case, able to mount on the wall with mounting holes on the back.
Comprehensive certificates: FCC, CE, RoHS(Certification received in early Sept)

Description

reComputer J2021 is built with , consisting of USB 3.1 ports(4x), M.2 key E for WIFI/BLE, M.2 Key M for SSD, RTC, CAN, Raspberry Pi GPIO 40-pin.

New Arrival: If you are looking for a full system that comes with industrial communications such as RS232/RS485. Please check our new industrial A203 and A205- E mini PCs, with pre-installed Jetpack 5.0.2, 128GB SSD, and WIFI/BT module, as also industrial interfaces.

: 1xRS232, 1 x RJ45 Gigabit Ethernet, 1x HDMI, 1x Audio Jack, 2x USB 3, 1x Micro USB, CAN, microSD Card Slot, reset button.
: 1x RS485, 1x RS232, 2xHDMI, 2x GbE, 4x USB3, CAN.

Ready for development

reComputer J2021 Mini PC is pre-installed with Jetpack, ideal for developing AI systems deployed at smart factories, automated optical inspection, and other AIoT embedded systems with entire and various for building fast and robust AI applications provided by Seeed Edge AI partners.

Edge Deployment made easy

reComputer J2021 built with Jetson Xavier NX module supports You can train a brand new custom model just in hours, or you can even use choose one of 130 pre-trained models from the always dashboard, deploy it to edge devices, and build a computer vision application within minutes! alwaysAI removes barriers to machine learning expertise requirements and makes creating computer vision apps easy, fast and effective.

With the deployment engine, you can OTA containerization and device monitoring in production mode, Run the application in offline mode and Auto-start the application on boot.

With an extensive library of , you can also customize any AI application, and also push real-time analytics to platforms such as Data Lakes and BI tools for further data visualization.

Seeed is a reseller of NVIDIA embedded systems and a preferred partner of the NVIDIA Jetson ecosystem for edge AI. Explore more carrier boards, full system devices, customization services, use cases, and developer tools at ! Welcome to check out our . We are looking forward to leveraging local and global resources to accelerate next-gen AI product together with you.

Comparison among reComputer J20 series and Official Dev Kits

Product			reComputer J2021	reComputer J2022
Module	Xavier NX (not production version)	Xavier NX 16GB (production version)	Jetson Xavier NX 8 GB	Jetson Xavier NX 16GB
AI Perf	21 TOPS
GPU	384-core NVIDIA Volta™ GPU
CPU	6-core NVIDIA Carmel ARM®v8.2 64-bit CPU 6 MB L2 4 MB L3
Memory	8 GB 128-bit LPDDR4x @ 51.2GB/s	16 GB 128-bit LPDDR4x @ 59.7GB/s	8 GB 128-bit LPDDR4x @ 59.7GB/s	16 GB 128-bit LPDDR4x 59.7GB/s
Storage	MicroSD (Card not included)	16 GB eMMC 5.1
Video encoder	2x 4K @ 30 \| 6x 1080p @ 60 \| 14x 1080p @ 30 (H.265/H.264)	2x 4K60 \| 4x 4K30 \| 10x 1080p60 \| 22x 1080p30 (H.265) 2x 4K60 \| 4x 4K30 \| 10x 1080p60 \| 20x 108p30 (H.264)
Video decoder	2x 4K @ 60 \| 4x 4K @ 30 \| 12x 1080p @ 60 \| 32x 1080p @ 30 (H.265) 2x 4K @ 30 \| 6x 1080p @ 60 \| 16x 1080p @ 30 (H.264)	2x 8K30 \| 6x 4K60 \| 12x 4K30 \| 22x 1080p60 \| 44x 1080p30 (H.265) 2x 4K60 \| 6x 4K30 \| 10x 1080p60 \| 22x 1080p30 (H.264)
Gigabit Ethernet	1*RJ45 Gigabit Ethernet Connector (10/100/1000)
USB	4 * USB 3.1 Type A Connector; 1 * Micro-USB port for Device mode;	4 * USB 3.0 Type A Connector; 1 * Micro-USB port for Device mode;	*4 USB 3.1 Type A Connector； 1* USB Type-C (Device mode)**
CSI Camera Connect	2*CSI Camera (15 pos, 1mm pitch, MIPI CSI-2 )
Display	1HDMI Type A; 1DP
FAN	1* FAN(5V PWM)
M.2 KEY E	1*M.2 Key E(WiFi/BT included)	1*M.2 Key E
M.2 KEY M	1*M.2 Key M
RTC	-	1*RTC Socket	RTC 2-pin RTC socket
Multifunctional port	1* 40-Pin header
Power Requirements	DC Jack 19V 4.74A (MAX 90W)		12V/5A(Barrel Jack 5.5/2.5mm)
Mechanical	103 mm x 90.5 mm x 31 mm	130mm x120mm x 50mm

Note

If use some GPIO libraries that causes floating voltage 1.2V~2V , GPIO issues on the carrier board could happen as the normal voltage should be 3V.
This is a common situation on the carrier boards, for both the reComputer series and official Nvidia Jetson developer kit.
Thus, aftersales / warrenty does not come into effect regarding this isssue.
For further information, refer to .

Application

For both beginners and experts, it is designed to help you to build your next-gen autonomous machine at the edge.

Edge AI Applications

reComputer J20 series, powered by Xavier NX, are ideal for building autonomous applications and complex AI tasks of image recognition, object detection, pose estimation, semantic segmentation, video processing, and many more.

- license plate detection
- car detection
- pedestrian detection
Industry 4.0:
- , , and custom PPE detection
Retail:
- sentiment analysis(: learn your customer with AI by Zenus smart camera),
Robotics:
Edge AI into the Wild:
Agriculture: weeding machine, Tractors, Livestock detection
Healthcare: medical imaging analysis

Find in the page tools and tutorials the community has created to power your development experience, and check out the page to inspire your next project!

AI Beginners learning center

If you would like to get critical AI skills and dive into deep learning. will be a good choice, which delivers practical, hands-on training and certification in AI at the edge for developers, educators, students, and lifelong learners. You can even earn certificates to demonstrate your understanding of Jetson and AI when you complete these free, open-source courses.

Please also check out Seeed guide including getting started with Jetson Nano and also building different projects.

Developers Tools

Pre-installed Jetpack for fast development and edge AI integration

begins with NVIDIA JetPack™ SDK which provides a full development environment and includes CUDA-X accelerated libraries and other NVIDIA technologies to kickstart your development. JetPack includes the Jetson Linux Driver package which provides the Linux kernel, bootloader, NVIDIA drivers, flashing utilities, sample filesystem, and toolchains for the Jetson platform. It also includes security features, over-the-air update capabilities, and much more.

Computer Vision and embedded machine learning

Seeed latest open-source project for deploying AI application within 3 nodes.
delivers a complete streaming analytics toolkit for AI-based multi-sensor processing and video and image understanding on Jetson.
, built on TensorFlow and PyTorch, is a low-code version of the NVIDIA TAO framework that accelerates the model training
: build, train, and deploy computer vision applications directly at the edge of reComputer. Get free access to 100 pre-trained Computer Vision Models and train custom AI models in the cloud in a