The Raspberry Pi AI HAT+ is an add-on board with a built-in Hailo AI accelerator forRaspberry Pi 5. It provides an accessible, cost-effective, and power-efficient way tointegrate high-performance AI. Explore applications including process control, security,home automation, and robotics.
The AI HAT+ is available in 13 and 26 tera-operations per second (TOPS) variants,built around the Hailo-8L and Hailo-8 neural network inference accelerators. The 13TOPS variant capably runs neural networks for applications including object detection,semantic and instance segmentation, pose estimation, and more. The 26 TOPS variantcan handle larger networks, can run them more quickly, and can more effectively runmultiple networks simultaneously
The AI HAT+ communicates using Raspberry Pi 5’s PCIe Gen 3 interface. When the hostRaspberry Pi 5 is running an up-to-date Raspberry Pi OS image, it automatically detectsthe on-board Hailo accelerator and makes the NPU available for AI computing tasks. Thebuilt-in rpicam-apps camera applications in Raspberry Pi OS natively support the AImodule, automatically using the NPU to run compatible post-processing tasks.
The micro:bit Drone:bit Kit has successfully combined micro:bit with drones, which has provided another possibility for students to create and explore in the sky. Through your operation, you can give it commands of hovering at a fixed altitude, flying from a waypoint, curvilinear flight, rolling in the sky, etc. even in the classrooms, get your first professional micro:bit Drone:bit Kit now!
Drone:bit BREAKTHROUGH—PROFESSIONAL GRADE
It is the first kind of drone equipped with optical flow locating in professional-grade which is able to hover indoors in a fixed point through programming in the world, with built-in optical flow sensors in high sensitivity and TOF sensors, they help to hover and locate in a more precise way. It is probably your first drone in professional grade that listen to your commands!
Drone:bit BREAKTHROUGH-FLYING SAFELY
The sealed propeller guards make sure your drone flies safely.
Drone:bit IN CLASSROOMS-AVAILABLE IN CLASSROOMS
Drone:bit could fly in the classrooms!
Drone:bit BREAKTHROUGH—CODE FOR MORE PROJECTS
Simple graphical and Python programming, available for complicated flying routines, flying gestures and rolling, etc., there are more possibilities waiting to be explored.
Drone:bit IN CLASSROOMS — FIND MORE IN WIKI
SPECIFICATION
product name
micro:bit Drone:bit Kit
Rated Voltage
3.7V
Battery Capacity
800mAh
Charging Voltage
5V
Charging Current
0.8A
Charging Port
Micro-USB
Power Protection
Over Charge/Discharge Protection
Propeller Guards
Support
LED
5 PCS (one for power indicator, four for status indicator)
Waypoints
Optical Flow
Fixing Altitude
Barometer + TOF
micro:bit Programming
Support
2.4G Remote Control Mode
Support
Flying Time
8min
Weight
509g
Flying Height
≤100m
The Raspberry Pi AI Kit bundles the Raspberry Pi M.2 HAT+ with a Hailo AI accelerationmodule for use with Raspberry Pi 5. It provides an accessible, cost-effective, and powerefficient way to integrate high-performance AI. Explore applications including processcontrol, security, home automation, and robotics. Contains:
• a Hailo AI module containing a Neural Processing Unit (NPU)• a Raspberry Pi M.2 HAT+, to connect the AI module to your Raspberry Pi 5• a thermal pad pre-fitted between the module and the M.2 HAT+• a mounting hardware kit• a 16mm stacking GPIO header
The AI module is a 13 tera-operations per second (TOPS) neural network inferenceaccelerator built around the Hailo-8L chip. The module uses the M.2 2242 form factor,and comes pre-installed in the M.2 HAT+, to which it connects through an M key edgeconnector. The M.2 HAT+ communicates between the AI module’s M.2 interface and theRaspberry Pi 5’s PCIe 2.0 interface.
When the host Raspberry Pi 5 is running an up-to-date Raspberry Pi OS image,it automatically detects the Hailo module and makes the NPU available for AI computingtasks. The built-in rpicam-apps camera applications in Raspberry Pi OS natively supportthe AI module, automatically using the NPU to run compatible post-processing tasks.