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reComputer J1010 – Nvidia Jetson Nano 4GB RAM + 16GB eMMC

9,850.00 EGP

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Availability: Out of stock
SKU:t-m61

J1010 is a hand-size edge AI box built with a Jetson Nano production module, rich set of IOs, aluminum case, passive heatsink, and pre-installed JetPack System, ready for your next AI application development and deployment.

PRODUCT DETAILS
Description

reComputer J1010 is a compact edge computer built with NVIDIA Jetson Nano 4GB  production module and comes with 128 NVIDIA CUDA® cores that deliver 0.5 TFLOPs (FP16) to run AI frameworks and applications like image classification, object detection, and speech processing. The production modules offer 16GB eMMC, a longer warranty, and 5-10 year operating life in a production environment(Jetson FAQ).

Besides the Jetson module, reComputer J1010 also includes J101 carrier board with onboard microSD card slot, 1*USB 3.0, 2*USB2.0, HDMI, M.2 Key E for WiFI, LTE and Bluetooth, RTC, Raspberry Pi GPIO 40-pin, and so on, as well as a heatsink, and aluminum case. The device has been pre-installed Jetpack 4.6.1, just plug in a USB C 5V/3A power supply, keyboard, mouse, and ethernet cable, and you are ready to start your embedded AI journey! 

We have included the microSD card slot on the carrier board of reComputer J1010. Please check the guide on boot image to a microSD card and adjust I/O speed.

Features
  • Hand-size edge AI full system delivering modern AI power of 0.5 TFLOPs (FP16)  and rich interfaces for embedded development. 
  • Ready for development and deployment: pre-installed NVIDIA JetPack supports the entire Jetson software stack and industry-leading AI developer tools for building robust AI applications such as logistics, retail, service, agriculture, smart city, healthcare, and life sciences, etc 
  • Power efficient: powered by Type C 5V/3A, consuming as little as 5 watts.
  • Expandable with the onboard interfaces and reComputer case, able to mount on the wall with mounting holes on the back.

 


If you are a beginner in Deep Learning,
 NVIDIA prepared this deep learning tutorial of Hello AI World and Two Days to a Demo. You can even earn certificates to demonstrate your understanding of Jetson and AI when you complete free, open-source courses. For most applications, you also need to connect with cameras, and you might need plug-and-play Grove sensors to use with Raspberry Pi HAT to extend more ideas.

Please also check out Seeed wiki guide including getting started guide also different projects such as use helmet detection and deploy a custom YOLOv5 model at Jetson Nano(fewer datasets, faster inference at 27FPS on reComputer J10 and 60FPS on J2021 of Jetson Xavier NX). 

Application

Find in the Jetson Community to inspire your next project!

If you work for an AI enterprise of ISV or system integrator, 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 products together with you.

 

Specifications:
Product reComputer J1010
Module Jetson Nano 4GB (production version)
Storage 16 GB eMMC
SD Card Slot Included (On the carrier board)
Video Encoder 4K30 | 2x1080p60 | 4x1080p30 | 4x720p60 | 9x720p30 

(H.265 & H.264)

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

(H.265 & H.264)

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

 

CSI Camera Connect 2*CSI Camera (15 pos, 1mm pitch, MIPI CSI-2 )
Display 1*HDMI Type A
FAN 1* FAN (5V PWM)
M.2 KEY E 1*M.2 Key E
RTC 1*RTC Socket
Multifunctional port 1* 40-Pin header
Power Supply USB-Type C 5V⎓3A
Mechanical 130 mm x 120 mm x 50 mm (with case)
Note

If use some GPIO libraries that cause a floating voltage of 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 computer series and the official Nvidia Jetson developer kit.
Thus, aftersales / warranty does not come into effect regarding this issue.
For further information, refer to NVIDIA official document.

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.

Hardware overview
Reference carrier board

Nearly the same functional design as the Jetson Nano Developer Kit. We have upgraded the carrier board with a micro SD card slot.

The old version

 

The latest version

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 edition cases like blue, silver, and silver metal, whose stackable structure allows you to stack more middle layers to create rooms very easily.

Part List
ACRYLIC COVER X1
Aluminum Frame x1
Jetson Nano module x1
Heatsink x1
J101 Carrier Board x1

We will not include a power supply

We will not include a 3V TC battery (CR1220)

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