Edge AI is bringing data processing directly onto devices instead of relying on cloud-based systems. The Learn Edge AI with Raspberry Pi bundle explores this approach in practice, combining Raspberry Pi hardware with a hands-on guide to building real systems. This approach makes Edge AI on Raspberry Pi practical for real-world use.

The setup uses the Raspberry Pi 5 together with the AI HAT+, an expansion board with an integrated Hailo accelerator. It connects via PCIe and is automatically detected by Raspberry Pi OS, making the neural processing unit available for AI tasks.

 

Raspberry Pi 5 AI HAT+

Vision-Based Applications with Camera Module 3

The bundle also includes the Raspberry Pi Camera Module 3, featuring a 12-megapixel sensor with HDR and autofocus. It supports both video and still image capture and is integrated through the libcamera framework.

Pi Cam Module v3

 

In the book, different camera options are covered, including official modules and USB webcams, as well as multi-camera setups.

From AI Fundamentals to Practical Setup

The book begins with the fundamentals of artificial intelligence and machine learning, including neural networks and the differences between Edge AI and cloud-based systems. It also addresses ethical considerations and future perspectives.

From there, the focus shifts to setting up the Raspberry Pi, installing the operating system, and working with Python in the Thonny IDE. Early examples include GPIO-based projects with LEDs and servo motors.

Detection, Tracking, and YOLO-Based Projects

Once the system is set up, the book moves on to AI pipelines such as person detection, pose estimation, instance segmentation, and depth estimation.
 

Detection of cows on a meadow

Further chapters introduce YOLO-based object detection, with examples including person detection alerts, people counting, and object recognition.

These examples show how Edge AI on Raspberry Pi can be applied to vision and control tasks.

From Detection to Physical Interaction

Later chapters extend these applications by connecting detection results to hardware. Gesture recognition is used to control servo motors and robotic mechanisms, including a robotic arm.

Additional sections cover the Hailo-8L accelerator, Python programming for AI projects, and troubleshooting.

A Practical Introduction to Edge AI

The bundle provides a structured path from basic concepts to working applications on the Raspberry Pi. It is aimed at readers who want to explore Edge AI and experiment with computer vision and embedded AI systems in a hands-on way.

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