
reComputer J2021-Edge AI Device with Jetson Xavier NX 8GB module, 4xUSB, M.2 Key E & Key M Slot, Aluminum case, Pre-installed JetPack System
J2021 is a hand-size edge AI box built with Jetson Xavier NX 8GB module which delivers up to 21 TOPs AI performance, rich set of IOs including USB 3.1 ports(4x), M.2 key E for WIFI, M.2 Key M for SSD, RTC, CAN, Raspberry Pi GPIO 40-pin, and so on, aluminum case, cooling fan, pre-installed JetPack System, as NVIDIA Jetson Xavier NX Dev Kit alternative, ready for your next AI application development and deployment
- 10+: $649.00
YOU MAY LIKE THIS
PRODUCT DETAILS
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 5.1.1, 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.
If you are looking for the version without power adapter, please check out reComputer J2021(w/o power adapter).
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 Jetson software stack and various developer tools 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 J202 carrier board, 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.
- A203 Mini PC: 1xRS232, 1 x RJ45 Gigabit Ethernet, 1x HDMI, 1x Audio Jack, 2x USB 3, 1x Micro USB, CAN, microSD Card Slot, reset button.
- Fanless A205-E Mini PC: 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 Jetson software stack and various developer tools 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 alwaysAI Accelerated Edge Deployment. 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 Python APIs, 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 Jetson Ecosystem
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 Seeed Jetson Ecosystem! Welcome to check out our free Edge AI partner program. 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 |
NVIDIA Jetson Xavier NX Developer Kit | reComputer J2012 | 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 | 1*HDMI Type A; 1*DP | |||
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 NVIDIA official document.
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.
- Traffic management
- license plate detection
- car detection
- pedestrian detection
- Industry 4.0:
- helmet detection, hard hat detection, and custom PPE detection
- visual anomaly detection using NVIDIA Deepstream IoT
- Retail:
- sentiment analysis(webinar: learn your customer with AI by Zenus smart camera),
- retail store items detection
- Robotics:
- Edge AI into the Wild: Wildfire detection
- Agriculture: weeding machine, Tractors, Livestock detection
- Healthcare: medical imaging analysis
Find in the Jetson Community Resources page tools and tutorials the community has created to power your development experience, and check out the Community Projects page to inspire your next project!
AI Beginners learning center
If you would like to get critical AI skills and dive into deep learning. NVIDIA’s Deep Learning Institute (DLI) 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 wiki guide including getting started with Jetson Nano and also building different projects.
Developers Tools
Pre-installed Jetpack for fast development and edge AI integration
Jetson software stack 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
- Edge AI no code Vision tool, Seeed latest open-source project for deploying AI application within 3 nodes.
- NVIDIA DeepStream SDK delivers a complete streaming analytics toolkit for AI-based multi-sensor processing and video and image understanding on Jetson.
- NVIDIA TAO tool kit, built on TensorFlow and PyTorch, is a low-code version of the NVIDIA TAO framework that accelerates the model training
- alwaysAI: 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 few clicks via enterprise subscription. Check out our wiki guide to get started with alwaysAI.
- Edge Impulse: the easiest embedded machine learning pipeline for deploying audio, classification, and object detection applications at the edge with zero dependencies on the cloud.
- Roboflow provides tools to convert raw images into a custom-trained computer vision model of object detection and classification and deploy the model for use in applications. See the full documentation for deploying to NVIDIA Jetson with Roboflow.
- YOLOv5 by Ultralytics: use transfer learning to realize few-shot object detection with YOLOv5 which needs only a very few training samples. See our step-by-step wiki tutorials
- Deci: optimize your models on NVIDIA Jetson Nano. Check webinar at Deci of Automatically Benchmark and Optimize Runtime Performance on NVIDIA Jetson Nano and Xavier NX Devices
Speech AI
- NVIDIA® Riva is a GPU-accelerated SDK for building Speech AI applications that are customized for your use case and deliver real-time performance.
Remote Fleet Management
Enable secure OTA and remote device management with Allxon. Unlock 90 days free trial with code H4U-NMW-CPK.
Robot and ROS Development
- NVIDIA Isaac ROS GEMs are hardware-accelerated packages that make it easier for ROS developers to build high-performance solutions on NVIDIA hardware. Learn more about NVIDIA Developer Tools
- Cogniteam Nimbus is a cloud-based solution that allows developers to manage autonomous robots more effectively. Nimbus platform supports NVIDIA® Jetson™ and ISAAC SDK and GEMs out-of-the-box. Check out our webinar on Connect your ROS Project to the Cloud with Nimbus.
Compare NVIDIA Jetson Nano and Jetson Xavier NX
With Jetson Nano, developers can use highly accurate pre-trained models from TAO Toolkit and deploy with DeepStream. Jetson Nano can achieve 11 FPS for PeopleNet- ResNet34 of People Detection, 19 FPS for DashCamNet-ResNet18 of Vehicle Detection, and 101 FPS for FaceDetect-IR-ResNet18 of Face Detection.
Jetson Xavier NX can achieve 172 FPS for PeopleNet- ResNet34 of People Detection, 274 FPS for DashCamNet-ResNet18 of Vehicle Detection, and 1126 FPS for FaceDetect-IR-ResNet18 of Face Detection. Benchmark details can be found on NVIDIA®’s DeepStream SDK website.
Reference: Jetson series benchmark for Deepstream: end-to-end application performance from data ingestion, decoding, image processing to inference
If you are developing an application that requires processioning multiple video streams at high resolution while performing ASR/NLP or other GPU-related tasks (CUDA enabled SLAM for example), then its deep learning accelerators can take on CNN inference and leave GPU for other tasks – TX2 or Jetson Nano maybe not satisfied. We recommend reComputer J2012 and J2021. Check our comparison blog here.
Hardware Overview
The interface-rich reference carrier board
Nearly the same functional design as Jetson Xavier NX Developer Kit
Seeed carrier board for reComputer J2021 is a high-performance, interface rich NVIDIA Jetson Xavier NX compatible carrier board, providing HDMI 2.0, Gigabit Ethernet, USB 3.1 Gen2, M.2 key E, M.2 key M, CSI camera, CAN, GPIO, I2C, I2S, fans, and other rich peripheral interfaces. It has the same functional design and size as the carrier board of NVIDIA® Jetson Xavier™ NX DEVELOPER KIT.
Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capability to all your embedded AI and edge systems.
Desktop, Wall Mount, Expandable or fit in anywhere
The back screw holes allow you to hang the product as you need. We also provide other editions case like blue, silver, and silver mental, whose stackable structure allows you to stack more middle layers to create rooms very easily.
Part List
- 1 x Acrylic Cover
- 1 x Aluminium Frame
- 1 x Jetson Xavier NX module
- 1 x Aluminum heatsink with fan
- 1 x Carrier board
- 1 x 12V/5A(Barrel Jack 5.5/2.5mm) Power Adapter (Power cable not included)
We will not include a power cord, please choose a suitable form according to your country.
We will not include a 3V RTC battery (CR1220)
Note
- We have already installed JetPack 5.1.1 system in the reComputer and you can directly use it by powering on.
- Please check our wiki for reflashing Jetpack and expanding the storage.
- We'd like to hear from you, welcome to join our Discord channel to share your thoughts (Jetson edge AI)
FAQ
1. What type of RTC is recommended for RTC socket?
CR1220 and ML1220. The non-rechargeable design of the RTC circuit of the carrier board allows both rechargeable and non-rechargeable RTC batteries to be used.
ECCN/HTS
HSCODE | 8471419000 |
USHSCODE | 8543708800 |
UPC | |
EUHSCODE | 8471800000 |
COO | CHINA |
CCATS | 1 |
CE | 1 |
EU DoC | 1 |
FCC | 1 |
KC | 1 |
REACH | 1 |
RoHS | 1 |
UK DoC | 1 |
UKCA | 1 |
LEARN AND DOCUMENTS
SHARED BY USERS
REVIEWS
-
from order viewawesome product
-
from order viewDoing great!