NVIDIA Jetson Nano Developer Kit - B01 Edition with Dual CSI Lanes - Box Expand

NVIDIA Jetson Nano Developer Kit - B01 Edition with Dual CSI Lanes

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9DEVJETSONNANOB

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The incredible NVIDIA Jetson Nano Developer Kit lets you dive headfirst into AI Development, allowing you to learn AI whilst Making awesome projects!

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Here at DIYElectronics, although we certainly love to fiddle and tinker with Electronics, sometimes we also like to go a bit deeper into the coding side, as hardware can only take projects so far before needing some software to take it further. This is why we have been making a concerted effort to bring in exciting new software-based electronics, with this NVIDIA Jetson Nano Developer Kit – The AI Computer Designed for Learning & Making – being one of the most exciting AI/IoT products that we’ve ever had the pleasure of carrying.

This awesome AI & Deep Learning Development Board is designed by the world-famous NVIDIA corporation, the inventors of the world’s first GPU, but instead of focussing on graphics like the graphics cards that many of us have in our personal computers, the NVIDIA Jetson Nano utilises the extremely capable GPU for parallel computing instead. This allows Makers to simultaneously Learn about AND Make AI and Machine Learning, with an absolute mountain-load of support and open-source software that is all meant to help both newbies and veterans in mastering the AI world. In fact, NVIDIA have done such an impressive job at providing support and resources for this platform that they have a comprehensive “Two Days to a Demo” Tutorial Project that anyone can utilise to create an entire deep learning project from absolute scratch, in as little as two days depending on how quickly you can grasp the concepts.

In terms of the actual functionality of the NVIDIA Jetson Nano, this board is capable of so much more than any Arduino or Raspberry Pi, with a core focus on AI Development, parallel computing and various machine learning processes like simulation generation, object identification and classification, as well as segmentation. This makes it an ideal board for learning all the in’s and out’s of machine learning, while also being able to cater to professional applications too – allowing you to learn, create, enhance, and then start the cycle over once again as you develop your skills and ultimately master the world of AI Frameworks and Deep Learning.

 

What’s New on the NVIDIA Jetson Nano B01 Edition?

If you don’t yet know how amazing the NVIDIA Jetson Nano is, then to start, you should definitely take a quick look through the original NVIDIA Jetson Nano Development Kit Page, as it offers a brief rundown of all of the key features of the powerful yet compact AI Dev’ Board. This is because this new B01 Edition is designed to almost the exact same specification, but has been upgraded now with an extremely handy secondary MIPI CSI connector for an additional camera. This opens up cool new possibilities for binocular (or stereoscopic) video input, allowing you to utilise 3D imaging in one direction, or to create extremely wide-angle vision at up to 360 degrees for even more monitoring, tracking and overall visual input. And while some may question just how valuable this upgrade is, there will certainly be some who understand that this “Minor New Feature” is a huge leap forward for a range of cool applications.

Please Note: While experimenting with one of the amazing boards, we found that it was best practice to plug all of the peripherals, displays and other extras in before plugging in the power. This is because the NVIDIA Jetson Nano automatically boots up once power is plugged in, and if some peripherals aren’t connected during startup, they may not behave like you expect.

 

NVIDIA Jetson Nano (B01 Edition) Developer Kit  -  Technical Specifications:

  • GPU                                                       

– 128-Core NVIDIA Maxwell

  • GPU Frequency (Typical)

– 921MHz

  • CPU

– 64-bit Quad-Core ARM Cortex-A57 MPCore

  • CPU Frequency (Typical)

– 1.43GHz

  • Memory (SO-DIMM)

– 4GB 64-bit LPDDR4 RAM

  • Memory Frequency

– 1600MHz

  • AI Performance

– 472 GFLOPs

  • Internal Storage

– N/A

  • External Storage

– MicroSD Card Support (Min. 16GB UHS-1)

  • Display Support

– HDMI 2.0

– DisplayPort 1.2 | eDP 1.4

  • Video Encoding Support

– H.264 / H.265

– 4K @ 30fps

– 4 x 1080p @ 30fps

– 9 x 720p @ 30fps

  • Video Decoding Support

H.264 / H.265

– 4K @ 60fps

– 2 x 4K @ 30fps

– 8 x 1080p @ 30fps

– 18 x 720p @ 30fps

  • USB Ports

– 4 x USB 3.0 Ports

  • Connectivity Support

– Gigabit Ethernet Support (PoE Capable)

– M.2 Slot (PCIe x1) for WiFi Card

– USB Ports for Dongles (Not All Dongles Supported)

  • Camera Support

2 x MIPI CSI-2 Port (IMX219 Camera Compatible)

  • Additional Interface Ports

– 3 x I2C Pin Sets

– 2 x SPI Pin Sets

– 1 x UART Pin Set

– 1 x I2S Pin Set

– 1 x 40-Pin GPIO Header (Raspberry Pi Layout)

  • Power Input (Micro USB)

– 5V 2A

  • Power Input (DC Barrel Jack)

– 5V 4A

  • Breakout Board Version

– A02 (Single MIPI Port | Includes UART Pins)

  • Included Extras

– Handy Foldout Paper Stand

– Quick Start Card

– Informational & Support Card

  • What You Will Need

– MicroSD Card (Minimum: 16GB UHS-1)

– 5V 2A Micro USB PSU // 5V 4A DC Barrel Jack PSU

– USB Keyboard & Mouse

– Computer Display (HDMI or DP Compatible)

– Access to Computer to Flash MicroSD Card

– USB or IMX219 Camera is Recommended

  • Included Warranty

– 1 Year: Be Sure to Keep Packaging

  • Weight (Packaged)

– ±250g

  • Dimensions (Core Module)

– 69.6 x 45mm

  • Dimensions (Assembled)

– 95.3 x 76.2mm

  • Dimensions (Packaged)

– 100 x 80 x 29mm

 

Additional Resources:

  • If you’re really eager to dive deep into the technical specifications, benchmarks and more in-depth details about this board, check out this NVIDIA Jetson Nano Dev’ Blog, which offers insights into almost anything you might need to know about this beautiful little computer.

  • Once you’ve gathered all of those juicy details, this next link is a “Two Days to a Demo” GitHub Page, which is a tutorial project designed to help you get a good grasp of machine learning, so that you can ideally deploy your first machine learning project in two days or less.

  • This next link is for those who already know what they’re doing, or for those who have completed the tutorial project in the previous link, and is the primary NVIDIA AI IoT GitHub Page, which is a true treasure trove of awesome resources, tools and more.

  • Finally, this is the Waveshare NVIDIA Jetson Nano Wiki Page, which offers even more links to great resources, forums and repositories, as well as links to further courses and development as well.

 

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