Quickstart - Use .NET to drive a Raspberry Pi Sense HAT

The Raspberry Pi Sense HAT (Hardware Attached on Top) is an add-on board for Raspberry Pi. The Sense HAT is equipped with an 8×8 RGB LED matrix, a five-button joystick, and includes the following sensors:

  • Gyroscope
  • Accelerometer
  • Magnetometer
  • Temperature
  • Barometric pressure
  • Humidity

This quickstart uses .NET to retrieve sensor values from the Sense HAT, respond to joystick input, and drive the LED matrix.


  • Raspberry Pi that supports ARM v7 instructions with Raspberry Pi OS. Raspberry Pi OS Lite (64-bit) is recommended.
  • Sense HAT

Prepare the Raspberry Pi

Use the raspi-config command to ensure your SBC is configured to support the following services:

  • SSH
  • I2C

For more information on raspi-config, refer to the Raspberry Pi documentation.

Attach the Sense HAT

With the Raspberry Pi device powered off, attach the Sense HAT. Power on the Raspberry Pi and launch the Bash shell once it boots. You may use SSH or connect the Raspberry Pi to a display.

Install Git

From the shell, ensure the latest version of Git is installed on your Raspberry Pi. Run the following commands:

sudo apt update
sudo apt install git

The commands use the Advanced Package Tool command to:

  • Download package information from all configured sources.
  • Install the Git command line tool.

Run the quickstart

From the shell, run the following command:

. <(wget -q -O - https://aka.ms/dotnet-iot-sensehat-quickstart)

The command downloads and runs a script. The script:

  • Installs the .NET SDK.
  • Clones a GitHub repository that includes the Sense HAT quickstart project.
  • Builds the project.
  • Runs the project.

Observe the console output as sensor data is displayed. The LED matrix displays a yellow pixel on a field of blue. Holding the joystick in any direction moves the yellow pixel in that direction. Clicking the center joystick button causes the background to switch from blue to red.

Get the source code

The source for this quickstart is available on GitHub.

Next steps