reComputer J1020 is a powerful and compact intelligent edge box built with Jetson Nano production module, bringing modern AI performance to the edge. The built-in carrier board is the same dimension as the Jetson Nano Developer Kit, including 4xUSB 3, M.2 Key M, HDMI, and DP. The full system also includes a fan and a power adapter.

For AI beginners, if you would like to get critical AI skills and dive into deep learning. NVIDIA’s Deep Learning Institute (DLI) delivers practical, hands-on training and certification. Please also check out Seeed wiki guide including getting started with Jetson Nano and also building different projects. 

For solution providers, reComputer J1020 is preinstalled with Jetpack 4.6.1, with rich set of I/Os, this AI box simplifies development and fits 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. 

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.

At Seeed Studio, 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.

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.

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, 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 NVIDIA 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.

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. 

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 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! 

• Pedestrian detection by Edge Impulse
• Hard hat detection and build custom PPE detection
• Pose Estimation with alwaysAI
• Visual anomaly detection using NVIDIA Deepstream IoT
• Retail store items detection
• Wildfire detection
• Animal detection 

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! 

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.