The Raspberry Pi AI HAT+ (26T) is an advanced add-on board designed to bring artificial intelligence (AI) capabilities to Raspberry Pi projects. Manufactured by Raspberry Pi, this HAT features a high-performance neural processing unit (NPU) optimized for machine learning tasks, enabling real-time AI inference on edge devices. It also includes GPIO pins for seamless integration with sensors, actuators, and other peripherals, making it ideal for AI-driven IoT applications.

• Image and Video Processing: Real-time object detection, facial recognition, and image classification.
• Natural Language Processing (NLP): Voice recognition and text-to-speech applications.
• Robotics: Autonomous navigation and decision-making for robots.
• IoT Devices: Smart home automation and edge AI applications.
• Industrial Automation: Predictive maintenance and quality control using AI.

The Raspberry Pi AI HAT+ (26T) is packed with features to support a wide range of AI and machine learning applications. Below are the key technical details:

The AI HAT+ connects to the Raspberry Pi via the standard 40-pin GPIO header. Below is the pin configuration for the HAT:

1. Attach the HAT to the Raspberry Pi: Align the 40-pin GPIO header on the HAT with the Raspberry Pi's GPIO pins and press gently to secure the connection.
2. Power the Raspberry Pi: The HAT draws power directly from the Raspberry Pi. Ensure the Raspberry Pi is powered via its USB-C port.
3. Install Required Software:
   • Update the Raspberry Pi OS:

     sudo apt update && sudo apt upgrade
     

   • Install the AI HAT+ drivers and SDK:

     sudo apt install ai-hat-plus-sdk
     

4. Connect Peripherals: Use the GPIO pins to connect sensors, cameras, or other devices as needed for your project.
5. Run AI Models: Deploy pre-trained machine learning models using the HAT's NPU for real-time inference.

• Cooling: The NPU generates heat during intensive tasks. Use a heatsink or fan for optimal performance.
• Power Supply: Ensure the Raspberry Pi's power supply can handle the additional load of the HAT.
• Software Compatibility: The AI HAT+ SDK supports TensorFlow Lite and ONNX models. Ensure your models are compatible.
• GPIO Usage: Avoid conflicts by checking the pin assignments of connected peripherals.

Below is an example Python script to perform object detection using the AI HAT+:

from ai_hat_plus import AIHAT import cv2

ai_hat = AIHAT()

model_path = "/home/pi/models/object_detection.tflite" ai_hat.load_model(model_path)

camera = cv2.VideoCapture(0)

while True: # Capture a frame from the camera ret, frame = camera.read() if not ret: print("Failed to capture frame. Exiting...") break

# Perform object detection
results = ai_hat.run_inference(frame)

# Display results on the frame
for obj in results:
    # Draw bounding boxes and labels
    x, y, w, h = obj['bbox']
    label = obj['label']
    confidence = obj['confidence']
    cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
    cv2.putText(frame, f"{label} ({confidence:.2f})", (x, y-10),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

# Display the frame
cv2.imshow("Object Detection", frame)

# Exit on pressing 'q'
if cv2.waitKey(1) & 0xFF == ord('q'):
    break

camera.release() cv2.destroyAllWindows()

1. HAT Not Detected:

   • Ensure the HAT is properly seated on the GPIO header.
   • Verify that the AI HAT+ drivers are installed correctly.

2. High Temperature:

   • Use a heatsink or fan to cool the HAT during intensive tasks.
   • Avoid running the HAT in environments exceeding 70°C.

3. Model Incompatibility:

   • Check that the model is in TensorFlow Lite or ONNX format.
   • Use the AI HAT+ SDK to convert unsupported models.

4. Power Issues:

   • Ensure the Raspberry Pi's power supply provides at least 3A at 5V.

• Q: Can I use the AI HAT+ with Raspberry Pi Zero?
  A: Yes, but performance may be limited due to the lower processing power of the Raspberry Pi Zero.

• Q: What is the maximum model size supported?
  A: The AI HAT+ supports models up to 512MB in size.

• Q: Does the HAT support multiple camera inputs?
  A: No, the HAT supports a single camera input via the Raspberry Pi's camera interface.

• Q: Can I use the HAT for training models?
  A: No, the HAT is designed for inference only. Use a more powerful system for training.

This concludes the documentation for the Raspberry Pi AI HAT+ (26T). For further assistance, refer to the official Raspberry Pi documentation or community forums.