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reComputer J1020- Edge AI Device with Jetson Nano module, Aluminium case, pre-installed JetPack System

SKU
110061361
Rating:
98% of 100
    J1020 is a hand-size edge AI box built with Jetson Nano module, rich set of IOs, aluminium case, passive heatsink, pre-installed JetPack System, ready for your next AI application development and deployment.
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    PRODUCT DETAILS

    Features

    • NVIDIA Jetson Nano Dev Kit alternative: hand-size Edge AI device built with Jetson Nano 4GB Production Module, the carrier board brings extensive I/Os: GPIO, CSI, Gigabit Ethernet, 4 x USB 3.0 Type A, 1 x Micro-USB, micro SD card is replaced with onboard 16 GB eMMC, Please check here for SSD storage expansion. 

    • 128 NVIDIA CUDA® cores deliver 0.5 TFLOPs (FP16) to run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.

    • Pre-installed Jetpack, JetPack SDK includes a board support package (BSP), Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries for deep learning, computer vision, GPU computing, multimedia processing, etc.

    • Support entire Jetson software stack and various developer tools for building fast and robust AI application provided by Seeed Edge AI partners.

    • Incredibly power efficient: powered by Type C 5V/3A, consuming as little as 5 watts.

    Description

    reComputer series for Jetson are compact edge computers built with NVIDIA advanced AI embedded systems: J10 (Nano 4GB) and J20 (Jetson Xavier NX 8GB and Jetson Xavier 16GB). With rich extension modules, industrial peripherals, and thermal management, reComputer for Jetson is ready to help you accelerate and scale the next-gen AI product by deploying popular DNN models and ML frameworks to the edge and inferencing with high performance, for tasks like real-time classification and object detection, pose estimation, semantic segmentation, and natural language processing (NLP). 


    At Seeed, you will find everything you want to work with NVIDIA Jetson Platform – official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, and edge devices, as well as accessories.

    Compare NVIDIA Jetson Nano Dev Kit B01 with reComputer J10 series 

    Product

    reComputer J1010

    reComputer J1020

    NVIDIA Jetson Nano Developer Kit-B01

    Module

    Jetson Nano 4GB (production version)

    Nano (not production version)

    Storage

    16 GB eMMC

    MicroSD (Card not included)

    Video Encoder

    4K30 | 2x1080p60 | 4x1080p30 | 4x720p60 | 9x720p30 

    (H.265 & H.264)

    4Kp30 | 4x 1080p30 | 9x 720p30 (H.264/H.265)

    Video Decoder

    4K60 | 2x 4K30 | 4x 1080p60 | 8x 1080p30 | 9x 720p60 

    (H.265 & H.264)

    4Kp60 | 2x 4Kp30 | 8x 1080p30 | 18x 720p30 (H.264/H.265)

    Gigabit Ethernet

    1*RJ45 Gigabit Ethernet Connector (10/100/1000)

    USB

    1 * USB 3.0 Type A; 

    2 * USB 2.0 Type A;

    1 * USB Type C for device mode;

    1 * USB Type C for 5V power input



    4 * USB 3.0 Type-A ;

    1 * Micro-USB port for device mode;

    4 * USB 3.0 Type-A; 

    1 * Micro-USB port for 5V power input  or for device mode

    CSI Camera Connect

    2*CSI Camera (15 pos, 1mm pitch, MIPI CSI-2 )

    Display

    1*HDMI Type A

    1*HDMI Type A; 

    1*DP

    1*HDMI Type A; 

    1*DP

    FAN

    1* FAN (5V PWM)

    M.2 KEY E

    1*M.2 Key E

    1*M.2 Key E (Disabled)

    1*M.2 Key E

    M.2 KEY M

    -

    1*M.2 Key M

    -

    RTC

    1*RTC Socket

    -

    Multifunctional port

    1* 40-Pin header

    Power

    USB-Type C 5V⎓3A;

    DC Jack 12V/2A

    DC Jack 5V⎓3A;

    Micro-USB 5V⎓2A

    Mechanical

    130 mm x 120 mm x 50 mm (with case)

    130mm x120mm x 50mm (with case)

    100 mm x 80 mm x 29 mm

    Application: for both beginners and experts, build your next-gen autonomous machine at the edge

    Edge AI Applications

    reComputer J1010 and J1020, powered by Jetson Nano, are ideal for learning AI  and building AI applications for image recognition, object detection, pose estimation, video processing, and many more. Check out the following application example with tutorials! 

    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

    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 are more recommend reComputer J20 powered by NVIDIA Jetson Xavier NX. Check our comparison blog here.

    Hardware Overview

    The interface-rich reference carrier board

    Nearly the same functional design as Jetson Nano Developer Kit

    Seeed reference carrier board for J1020 is a high-performance, interface-rich NVIDIA Jetson Nano compatible carrier board, providing HDMI 2.0, Gigabit Ethernet, USB 3.0, USB 2.0, CSI camera, GPIO, I2C, I2S, fans, and other rich peripheral interfaces. 

    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.


    Note

    • Name change: 'reComputer Jetson-10-1-H0' has changed to 'reComputer J1020'.
    • We have already installed JetPack 4.6 system in the reComputer and you can directly use it by powering in.
    • 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

    Part List

    Acrylic Coverx1
    Aluminum Frame x1
    Jetson Xavier NX module x1
    Heatsink x1
    A206 Carrier board x1

    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).

    ECCN/HTS

    HSCODE 8471419000
    USHSCODE 8471490000
    UPC
    FCC 1
    CE 1

    LEARN AND DOCUMENTS

    Learn

    Zenus leverages the power of Artificial Intelligence to create incredible products while driving the ethical use of facial analysis. Seeed supports the Zenus AI camera with Seeed's high-performance, interface-rich NVIDIA Jetson Nano/Xavier NX/TX2 NX compatible carrier board.
    MaskCam is a prototype reference design for a Jetson Nano-based smart camera system that measures crowd face mask usage in real-time, with all AI computation performed at the edge. MaskCam detects and tracks people in its field of view and determines whether they are wearing a mask via an object detection, tracking, and voting algorithm.
    We represent you the user guide of reComputer Jetson Series, providing kickstart for the beginners, documentation for usage, elaboration for the advance, AI tools and projects for reference, comprehensively help you from beginner to advancer.
    You can securely manage NVIDIA® JetPack 4.6 onward versions with Cyber Security at the Edge protecting all networks and hardware. Here are some operations about installing, getting code, adding devices etc.
    Seeed is glad to partner with Allxon to deliver a secure remote management solution for Jetson Platform. At Seeed, you will find everything you want to work with NVIDIA Jetson Platform – official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, and kits, as well as third-party boards and accessories.

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    REVIEWS

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    1. Product Quality
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      A lot of helpful tutorials and tools on the wiki and web that can save a lot of time getting started. Everything is as described
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    2. Product Quality
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      amazing how fast Jetson Nano is compared to the Rpi 3B+ that I have been using. if you are familiar with Ubuntu Linux, you will not have any problems. Jetson Nano Dev kit was $99 but everywhere is out of stock. It is still a great value for $199 as the production module is $129 already and compare to others on Amazon.
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    3. Product Quality
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      The board works great and I like it. I have other ARM SBCs, Khadas VIM3, and Raspberry Pi 4. Pi has excellent community but is vastly under computing power.
      It boots from the onboard eMMC, but also has an M.2 slot for adding SSD.
      Nice board for AI tinker!
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    4. Product Quality
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      Support team is very responsive, nice board for object detection application development.
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    5. Product Quality
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      Documentation
      80%
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