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How to Use Jetson nano : Examples, Pinouts, and Specs

Image of Jetson nano
Cirkit Designer LogoDesign with Jetson nano in Cirkit Designer

Introduction

The NVIDIA Jetson Nano is a small yet powerful computer designed specifically for artificial intelligence (AI) and machine learning (ML) applications. It features a quad-core ARM Cortex-A57 CPU and a 128-core Maxwell GPU, making it an excellent choice for robotics, embedded systems, and edge AI projects. The Jetson Nano provides developers with the computational power needed to run modern AI frameworks and process high-resolution sensor data in real-time, all while maintaining a compact and energy-efficient design.

Explore Projects Built with Jetson nano

Use Cirkit Designer to design, explore, and prototype these projects online. Some projects support real-time simulation. Click "Open Project" to start designing instantly!
Jetson Nano-Based Smart Fan with USB Connectivity
Image of skematik: A project utilizing Jetson nano  in a practical application
This circuit powers a Jetson Nano and a fan using a 220V AC power supply. The power supply converts the AC voltage to DC, which is then distributed to the Jetson Nano via a converter jack and to the fan. Additionally, a Jete w7 USB device is connected to the Jetson Nano.
Cirkit Designer LogoOpen Project in Cirkit Designer
Arduino Nano and nRF24L01 Wireless Controlled Robotic Platform
Image of Wheel ChAIR: A project utilizing Jetson nano  in a practical application
This circuit is a wireless controlled robotic vehicle system. It features two Arduino Nanos with nRF24L01 modules for remote communication, a joystick for control input, and a L298N motor driver to operate two DC gearmotors. Power is managed by 18650 Li-Ion batteries and 7805 voltage regulators, with rocker switches for power control.
Cirkit Designer LogoOpen Project in Cirkit Designer
Arduino Nano-Based Quadcopter with NRF24L01 Wireless Control and MPU-9250 Sensor
Image of Drone Circuit: A project utilizing Jetson nano  in a practical application
This circuit is a quadcopter control system that uses an Arduino Nano to manage four brushless motors via Electronic Speed Controllers (ESCs). It includes an NRF24L01 wireless module for remote communication and an MPU-9250 sensor for orientation and motion sensing, all powered by a LiPo battery through an XT60 power distribution board.
Cirkit Designer LogoOpen Project in Cirkit Designer
Arduino Nano-Based Drone Remote Control with NRF24L01 Wireless Communication
Image of Arduino Transmitter and receiver: A project utilizing Jetson nano  in a practical application
This circuit is a wireless drone control system utilizing two Arduino Nano microcontrollers. One Arduino Nano is configured as a transmitter with a joystick module, potentiometer, pushbuttons, and an NRF24L01 module for sending control signals. The other Arduino Nano acts as a receiver, interfacing with a corresponding NRF24L01 module to receive the transmitted signals, and it includes a buzzer for audio feedback. The system is powered by a 2x 18650 battery pack with voltage regulation provided by an AMS1117 3.3V regulator and an electrolytic capacitor for smoothing.
Cirkit Designer LogoOpen Project in Cirkit Designer

Explore Projects Built with Jetson nano

Use Cirkit Designer to design, explore, and prototype these projects online. Some projects support real-time simulation. Click "Open Project" to start designing instantly!
Image of skematik: A project utilizing Jetson nano  in a practical application
Jetson Nano-Based Smart Fan with USB Connectivity
This circuit powers a Jetson Nano and a fan using a 220V AC power supply. The power supply converts the AC voltage to DC, which is then distributed to the Jetson Nano via a converter jack and to the fan. Additionally, a Jete w7 USB device is connected to the Jetson Nano.
Cirkit Designer LogoOpen Project in Cirkit Designer
Image of Wheel ChAIR: A project utilizing Jetson nano  in a practical application
Arduino Nano and nRF24L01 Wireless Controlled Robotic Platform
This circuit is a wireless controlled robotic vehicle system. It features two Arduino Nanos with nRF24L01 modules for remote communication, a joystick for control input, and a L298N motor driver to operate two DC gearmotors. Power is managed by 18650 Li-Ion batteries and 7805 voltage regulators, with rocker switches for power control.
Cirkit Designer LogoOpen Project in Cirkit Designer
Image of Drone Circuit: A project utilizing Jetson nano  in a practical application
Arduino Nano-Based Quadcopter with NRF24L01 Wireless Control and MPU-9250 Sensor
This circuit is a quadcopter control system that uses an Arduino Nano to manage four brushless motors via Electronic Speed Controllers (ESCs). It includes an NRF24L01 wireless module for remote communication and an MPU-9250 sensor for orientation and motion sensing, all powered by a LiPo battery through an XT60 power distribution board.
Cirkit Designer LogoOpen Project in Cirkit Designer
Image of Arduino Transmitter and receiver: A project utilizing Jetson nano  in a practical application
Arduino Nano-Based Drone Remote Control with NRF24L01 Wireless Communication
This circuit is a wireless drone control system utilizing two Arduino Nano microcontrollers. One Arduino Nano is configured as a transmitter with a joystick module, potentiometer, pushbuttons, and an NRF24L01 module for sending control signals. The other Arduino Nano acts as a receiver, interfacing with a corresponding NRF24L01 module to receive the transmitted signals, and it includes a buzzer for audio feedback. The system is powered by a 2x 18650 battery pack with voltage regulation provided by an AMS1117 3.3V regulator and an electrolytic capacitor for smoothing.
Cirkit Designer LogoOpen Project in Cirkit Designer

Common Applications and Use Cases

  • Robotics and autonomous systems
  • Computer vision and image processing
  • Natural language processing (NLP)
  • Smart home and IoT devices
  • Edge AI for real-time data analysis
  • AI-powered drones and surveillance systems

Technical Specifications

Key Technical Details

Specification Details
CPU Quad-core ARM Cortex-A57
GPU 128-core NVIDIA Maxwell
Memory 4 GB LPDDR4
Storage microSD card slot (user-provided)
Connectivity Gigabit Ethernet, GPIO, I2C, I2S, SPI, UART
Power Input 5V/4A (via barrel jack or micro-USB)
Operating System Ubuntu-based NVIDIA JetPack SDK
Dimensions 100 mm x 80 mm
Weight ~140 grams

Pin Configuration and Descriptions

The Jetson Nano features a 40-pin GPIO header, similar to the Raspberry Pi, for interfacing with external devices. Below is a summary of the pin configuration:

Pin Number Pin Name Description
1 3.3V Power 3.3V power output
2 5V Power 5V power output
3 GPIO2 (I2C SDA) General-purpose I/O or I2C data line
4 5V Power 5V power output
5 GPIO3 (I2C SCL) General-purpose I/O or I2C clock line
6 Ground Ground
7 GPIO4 General-purpose I/O
8 GPIO14 (UART TX) UART transmit line
9 Ground Ground
10 GPIO15 (UART RX) UART receive line
... ... ... (Refer to the official pinout diagram)

For the full pinout, refer to the official NVIDIA Jetson Nano documentation.

Usage Instructions

How to Use the Jetson Nano in a Circuit

  1. Powering the Jetson Nano:

    • Use a 5V/4A power supply via the barrel jack for optimal performance.
    • Alternatively, power the device via the micro-USB port (not recommended for high-power applications).
  2. Connecting Peripherals:

    • Attach a monitor via the HDMI or DisplayPort interface.
    • Connect a keyboard and mouse to the USB ports.
    • Insert a microSD card with the JetPack OS pre-installed.
  3. Interfacing with GPIO:

    • Use the 40-pin GPIO header to connect sensors, actuators, or other peripherals.
    • Ensure proper voltage levels (3.3V logic) to avoid damaging the board.
  4. Running AI Models:

    • Install AI frameworks like TensorFlow, PyTorch, or OpenCV using the JetPack SDK.
    • Deploy pre-trained models or train your own using the GPU for acceleration.

Important Considerations and Best Practices

  • Cooling: Attach a heatsink or fan to prevent overheating during intensive tasks.
  • Power Supply: Use a reliable power source to avoid instability or performance throttling.
  • Static Protection: Handle the board with care to prevent electrostatic discharge (ESD) damage.
  • Software Updates: Regularly update the JetPack SDK to access the latest features and security patches.

Example: Using the Jetson Nano with an Arduino UNO

The Jetson Nano can communicate with an Arduino UNO via UART. Below is an example Python script to send data from the Jetson Nano to the Arduino:

import serial
import time

Initialize serial communication with the Arduino

Replace '/dev/ttyTHS1' with the correct UART port on the Jetson Nano

arduino = serial.Serial('/dev/ttyTHS1', baudrate=9600, timeout=1)

Wait for the connection to initialize

time.sleep(2)

Send data to the Arduino

try: while True: arduino.write(b'Hello, Arduino!\n') # Send a message print("Message sent to Arduino") time.sleep(1) # Wait 1 second before sending the next message except KeyboardInterrupt: print("Exiting program") finally: arduino.close() # Close the serial connection


**Note**: Ensure the Jetson Nano's UART pins are connected to the Arduino's RX and TX pins, and that both devices share a common ground.

Troubleshooting and FAQs

Common Issues and Solutions

  1. Jetson Nano does not boot:

    • Ensure the microSD card is properly inserted and contains a valid JetPack OS image.
    • Verify the power supply provides sufficient current (5V/4A recommended).
  2. Overheating during operation:

    • Attach a heatsink or active cooling fan to the module.
    • Avoid running intensive tasks for extended periods without proper cooling.
  3. GPIO pins not responding:

    • Check the pin configuration and ensure the correct pin mode is set in your code.
    • Verify that the connected device operates at 3.3V logic levels.
  4. No display output:

    • Confirm the HDMI/DisplayPort cable is securely connected.
    • Ensure the monitor is powered on and set to the correct input source.

FAQs

Q: Can I power the Jetson Nano via USB?
A: Yes, but it is not recommended for high-power applications as USB power may cause instability.

Q: What AI frameworks are supported?
A: The Jetson Nano supports popular frameworks like TensorFlow, PyTorch, Caffe, and OpenCV.

Q: Can I use the Jetson Nano for real-time object detection?
A: Yes, the 128-core Maxwell GPU provides sufficient power for real-time object detection using models like YOLO or SSD.

Q: How do I update the JetPack SDK?
A: Use the NVIDIA SDK Manager on a host PC to download and flash the latest JetPack version to the microSD card.

For additional support, refer to the official NVIDIA Jetson Nano forums and documentation.