NVIDIA Jetson Nano : Features, Specifications, Architecture, Working, Differences & Its Applications

NVIDIA introduced the Jetson family, a part of NVIDIA’s embedded systems, designed to provide the required hardware & software to develop AI-powered systems and devices. There are different types of NVIDIA Jetson boards, like Jetson TX2 Series, Jetson Xavier NX, Jetson Nano, AGX Xavier Series, Xavier NX Developer Kit & AGX Xavier Industrial. The Jetson Nano was introduced by NVIDIA in 2019 as a low-cost alternative to other Jetson boards. Thus, this board is specially targeted to provide a balance of affordability and performance in embedded systems and edge AI. This article elaborates on NVIDIA Jetson Nano, its working, and applications.

What is NVIDIA Jetson Nano?

The NVIDIA Jetson Nano is a low-cost, powerful, and compact single-board computer designed to bring machine learning and GPU-accelerated AI capabilities to edge devices. It is a part of the Jetson family, but it is specially aimed at developers, hobbyists, and entry-level users who want to design AI-powered projects at a lower price. In addition, it is an affordable and low-power platform that allows students, makers, and developers to experiment with and deploy AI models for a variety of applications, such as object detection, speech processing, and image classification.

Features

The features of NVIDIA Jetson Nano include the following.

• It is a small and powerful computer.
• It provides a good balance of power efficiency and performance.
• The Jetson Nano Developer Kit has the Nano module & a carrier board, which makes it suitable for prototyping & developing AI products.
• This module handles a variety of AI workloads like image classification, speech processing, and object detection.
• In addition, it runs several neural networks concurrently by allowing for complex AI tasks.
• It is designed for edge computing, thus compatible for applications like smart cameras, industrial automation, robotics, and many more.
• The Developer Kit offers a platform for prototyping & AI applications testing before deployment.
• It is available with the JetPack SDK with libraries for computer vision, deep learning, & multimedia processing.
• It provides a range of interfaces like GPIO, UART, I2C, USB, camera connectors & Ethernet.
• The Jetson Nano has low-power consumption.

Specifications

The NVIDIA Jetson Nano specifications include the following.

• CPU Model is Quad-core ARM Cortex-A57.
• Clock speed is 1.43 GHz.
• Architecture is 64-bit ARMv8.
• Core count is 4 cores.
• GPU Model is a 128-core NVIDIA Maxwell GPU.
• It has 128 CUDA Cores.
• Performance is ~472 GFLOPs.
• Its memory capacity is 4 GB LPDDR4.
• Bandwidth is 25.6 GB/s.
• In addition, it has a MicroSD card slot to support external storage devices through USB & the GPIO header.
• It has a Gigabit Ethernet port and needs an external Wi-Fi dongle.
• It has USB Ports like a USB 3.0 Type-A port, a USB 2.0 Micro-B, and a USB 2.0 Type-A.
• It has Display Outputs like HDMI 2.0 & DP 1.2 through the GPIO header.
• This AI computer has an MIPI CSI-2 Camera Connector, which supports up to 12 MP cameras.
• It supports I2S Audio for audio I/O through GPIO.
• Its 40-pin GPIO header supports multiple interfaces like I2S, I2C, UART, SPI, and PWM.
• Input power supply is DC 5V/4A via micro-USB or barrel jack.
• Maximum power consumption is ~10 watts.
• It supports Linux OS for Tegra (L4T) based on Ubuntu 18.04.
• It supports NVIDIA deep learning AI platform, TensorFlow, PyTorch & other ML frameworks.
• In addition, it has frameworks, tools, and libraries for computer vision, deep learning, and AI applications like
• TensorRT, CUDA, OpenCV, and cuDNN.
• This computer runs AI models with up to 472 GFLOPs.
• It supports both INT8 precision and FP16 for deep learning models to exploit performance within AI tasks.
• Its operating temperature ranges from 0°C to 50°C, and storage temperature ranges from -25°C to 80°C.

How does NVIDIA Jetson Nano Work?

The NVIDIA Jetson Nano module works by providing a powerful and compact computing platform. So this module integrates a GPU, CPU, and other necessary hardware components. Thus, it allows managing machine learning and artificial intelligence tasks, particularly at the edge. This is mainly useful in smart cameras, drones, robotics & other embedded applications, wherever low power consumption and real-time data processing are necessary.

NVIDIA Jetson Nano Architecture

The NVIDIA Jetson Nano module is a low-power and small single-board computer designed mainly for edge AI applications. So it is a part of the Jetson family, which is designed to run robotics, AI models & other embedded systems. Thus, the NVIDIA Jetson Nano architecture includes several key components, where each component plays a major role in its operation. Thus, this architecture’s breakdown & its functions are discussed below.

NVIDIA Jetson Nano Architecture

Processor

NVIDIA Jetson Nano includes CPU & GPU processors, which are discussed below.

The Jetson Nano utilizes a Quad-core ARM Cortex-A57 CPU, which runs at 1.43 GHz. Its architecture is ARMv8 64-bit with 1.43 GHz CLK speed per core. So the main role of this CPU is to handle general-purpose computing tasks like user-level applications, system management, & some background tasks that don’t need parallel processing power.

The GPU is a Maxwell architecture by NVIDIA with 128 CUDA cores. These are the parallel computing cores that speed up computational workloads, particularly those related to machine learning, AI, and graphics tasks. Thus, the GPU is essential for tasks that need heavy parallelization, like AI inference, computer vision, image processing, video rendering, etc. In addition, it handles Tensor operations for deep learning models with PyTorch or TensorFlow frameworks.

Memory

The Jetson Nano includes a 4 GB LPDDR4 RAM that provides decent memory bandwidth, mainly for AI applications and many other tasks. The largest amount of memory can be optimized for AI and edge computing at low power.

The main role of RAM is to store and access data and programs quickly, which are currently in use by the GPU and CPU. The quantity of memory plays an essential role in the performance of memory-intensive applications like processing large images or videos, and AI model inference.

Storage

This microSD card works as the main storage for the system. So this module relies on a microSD card for OS booting & storing files. Generally, the microSD card must be a minimum of 16 GB UHS-1 rated for the operating system & applications.

Connectivity

The NVIDIA Jetson Nano includes a Gigabit Ethernet port used for high-speed networking. So this is essential for applications that need real-time data transfer. So it has 4 USB 3.0 ports, like micro-USB – 1 for power, and a full-size USB-3 allows you to connect peripherals like keyboards, cameras, etc.

This module doesn’t have Wi-Fi, but you can connect a Wi-Fi dongle through one of the USB ports. The Nano module includes an HDMI 2.0 port mainly for video output. In addition, it can also have a MIPI CSI-2 camera connector, which connects a camera module.

Power Supply

The Nano module uses a 5V/4A power supply. So it can be provided either through the GPIO pins or the micro-USB port. Thus, this module is designed to be energy-efficient, which runs at approximately 5W typical load & max up to 10Watts.

I/O & Expansion

This module has a 40-pin GPIO header which connects motors, sensors & other peripheral devices. So it doesn’t have an in-built PCIe slot; however, there is a PCIe Gen2 x1 lane accessible through the GPIO header.

Its 40-pin GPIO Header is well-matched with the Raspberry Pi pinout, which provides access to a variety of GPIO pins for actuator, peripheral, and sensor connectivity. Thus, this allows for interfacing with sensors, motors, LEDs, and many more.

The GPIO header also has different communication protocols like SPI, I2C, PWM, and UART for interacting with other devices or electronic components. So, PCIe Gen2 x1 Lane is exposed on the 40-pin header.

Thermal Management

The Jetson Nano module has a tiny heatsink on the GPU or CPU to manage heat. This module can also be equipped with an exterior fan for extra cooling for more severe tasks like AI models running or heavy image processing.

Software Interfaces

The Jetson Nano module runs on a Linux OS based on Ubuntu, which is optimized for NVIDIA hardware that allows simple access to powerful software libraries. It uses CUDA-accelerated libraries or deep learning libraries like TensorRT, cuDNN & other GPU-accelerated tools to accelerate computations.

NVIDIA Jetson Nano Software

The JetPack SDK is NVIDIA Jetson Nano’s software, which is a complete development kit used in robotics & embedded AI applications. This module includes a full desktop Linux environment and a set of libraries for computer vision, deep learning, multimedia, etc. Thus, developers can be easily allowed to develop & set up AI solutions on the Jetson Nano module.

• JetPack SDK is the core software package that provides the operating system, APIs, libraries, pre-built samples, and developer tools.
• JetPack software has optimized libraries like TensorRT, OpenCV, and cuDNN, which are essential for computer vision and high-performance AI inference tasks.
• This module supports very famous deep learning frameworks like PyTorch, Caffe, and TensorFlow, which allow developers to use their existing AI models.
• JetPack software provides libraries & tools for different computer vision tasks, which include image classification, video processing, and object detection. Thus, it is suitable for a variety of applications like smart cameras and robotics.
• The Jetson Nano module has hardware acceleration for video encoding & decoding, which allows multimedia processing for video analytics applications.
• The tools in this software debug and deploy applications on the Jetson Nano module to streamline the development procedure.
• The Jetson Nano module profits from an active and large developer community with various open-source projects & resources obtainable for learning & building.
• The software ecosystem of the Jetson Nano module is centered on the JetPack SDK. Thus, it provides the necessary tools & resources to control the AI & computing capabilities of the device for a broad range of embedded applications.

Jetson Nano Vs Jetson Xavier NX

The Jetson Nano & Jetson Xavier NX are both Jetson modules by NVIDIA, but the Xavier NX provides more advanced features and significantly higher performance. Thus, the difference between these two modules is discussed below.

Advantages

The advantages of NVIDIA Jetson Nano include the following.

• NVIDIA Jetson Nano is affordable, lightweight, and compact.
• It is power-efficient, like ~10W.
• It supports AI frameworks like PyTorch, TensorFlow, OpenCV, and many more.
• It provides real-time AI processing with GPU acceleration at the edge.
• In addition, it provides extensive I/O & hardware interfacing like USB, GPIO, camera, and many more.
• It provides a scalable platform mainly for better AI applications.
• This board allows AI application development with NVIDIA JetPack SDK
• In addition, this board can also support a whole GPU-accelerated NVIDIA software stack, mainly for application development & optimization
• It has a large community support with a wide set of tutorials for beginners.
• It uses a large heat sink for better heat dissipation.

Disadvantages

The disadvantages of NVIDIA Jetson Nano include the following.

• The Jetson Nano is expensive than a Raspberry Pi.
• It lacks built-in Bluetooth and WiFi.
• This board has limited USB 3.0 ports & single Gigabit Ethernet port, which potentially limits the number of peripherals that can be connected.
• In addition, it may need a separate power supply, particularly while using the complete GPU capabilities & potentially a cooling system for continued high performance.
• Sometimes, Jetson Nano struggles with the most recent TensorFlow or PyTorch versions.
• This module has only two PWM pins.

Applications

The applications of NVIDIA Jetson Nano include the following.

• The Jetson Nano module can power robotics with insight capabilities to detect and avoid many objects in its path, process images & build maps in real-time.
• It can be incorporated into robotic arms for different tasks like object grasping & placement, particularly in industrial settings.
• This module analyzes video feeds to recognize unusual activity, notice faces, and activate alerts for possible threats.
• It performs various tasks like crowd monitoring, license plate recognition & improving safety systems.
• It analyzes video content to help security staff react more effectively to possible incidents.
• It processes data locally on IoT devices, decreasing latency & bandwidth usage.
• In addition, this module can be used within smart city applications like waste management, traffic monitoring, and industrial IoT for analytical maintenance & process optimization.
• It acts as an intelligent gateway to collect & gather data from various sensors & devices.
• The Jetson Nano module can categorize images with high accuracy, recognizing scenes, objects & other visual elements.
• It detects and locates objects in video streams or images for many AI applications.
• It can process & analyze audio data in voice control & speech recognition.
• In addition, it can be used by farmers for early pest detection, increasing crop yields, and optimizing resource use.
• This module can be used for tasks like customer behavior analysis and shelf monitoring in retail environments.
• It can be used within medical imaging for various tasks like assisting with diagnoses and analyzing scans.

Conclusion:

Thus, this is an overview of the NVIDIA Jetson Nano module, which is a powerful and small single-board computer. It is mainly designed for AI and edge computing applications. In addition, this is an affordable and low-power platform that allows makers, developers & students to test with & arrange AI models for a variety of applications like object detection, speech processing, and image classification. Here is a question for you: What is NVIDIA Jetson?