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This hands-on bundle lets you build real Edge AI applications with the Raspberry Pi Raspberry Pi AI HAT+ (13 TOPS) The Raspberry Pi AI HAT+ (13 TOPS) is an expansion board designed for the Raspberry Pi 5, featuring an integrated Hailo AI accelerator. This add-on offers a cost-effective, efficient, and accessible approach to incorporating high-performance AI capabilities, with applications spanning process control, security, home automation, and robotics. The AI HAT+ connects via the Raspberry Pi 5’s PCIe Gen3 interface. When the Raspberry Pi 5 is running a current version of the Raspberry Pi OS, it automatically detects the onboard Hailo accelerator, making the neural processing unit (NPU) available for AI tasks. Additionally, the rpicam-apps camera applications included in Raspberry Pi OS seamlessly support the AI module, automatically using the NPU for compatible post-processing functions. Raspberry Pi Camera Module 3 Raspberry Pi Camera Module 3 is a compact camera from Raspberry Pi. It offers an IMX708 12-megapixel sensor with HDR, and features phase detection autofocus. Camera Module 3 is available in standard and wide-angle variants, both of which are available with or without an infrared cut filter. Camera Module 3 can be used to take full HD video as well as stills photographs, and features an HDR mode up to 3 megapixels. Its operation is fully supported by the libcamera library, including Camera Module 3’s rapid autofocus feature: this makes it easy for beginners to use, while offering plenty for advanced users. Camera Module 3 is compatible with all Raspberry Pi computers. Book: Edge AI Made Practical – AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. This bundle contains: Book: Edge AI Made Practical Raspberry Pi AI HAT+ (13 TOPS) Raspberry Pi Camera Module 3 Active Cooler for Raspberry Pi 5 FPC Display Cable for Raspberry Pi 5 (300 mm) Elektor Component Kit 40-pin GPIO Header Traffic Light Module LED red 5 V with built-in resistor LED yellow 5 V with built-in resistor LED green 5 V with built-in resistor LED blue 5 V with built-in resistor Breadboard (400 Tie-points) 10 Dupont wires male-female DHT22 sensor module Servo motor Required Raspberry Pi 5

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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This bundle contains the AI Fusion Lab Kit – which includes over 450 components – and the book Physical AI with Raspberry Pi, offering a comprehensive, hands-on introduction to AI, electronics, and Python programming. Build practical projects that combine computer vision, voice interaction, sensors, motors, and large language models. The included book guides you step by step from Raspberry Pi setup and hardware control to advanced applications using OpenCV, MediaPipe, YOLO, OpenAI services, and local Ollama models. SunFounder AI Fusion Lab Kit for Raspberry Pi (450+ parts) The AI Fusion Lab Kit transforms a Raspberry Pi into a complete platform for learning artificial intelligence, electronics, and Python programming. It supports Raspberry Pi 5, 4B, 3B+, 3B, and Zero 2 W, as well as popular AI models and services including ChatGPT, Gemini, Grok, DeepSeek, Qwen, Doubao, and Ollama. With its camera, Pan-Tilt HAT, 10-axis sensor module, microphone, speaker, and electronic components, the kit enables users to build interactive AI projects that combine voice, vision, movement, and sensor data. It is suitable for beginners, students, makers, and anyone who wants to explore practical AI applications. Build Multimodal AI Projects Combine large language models with speech recognition, text-to-speech, camera vision, sensors, and breadboard circuits. Create projects that can listen, speak, see, react, and interact with their environment while learning how modern AI systems work. Explore AI Vision and Object Tracking Use YOLO, OpenCV, and MediaPipe to detect and track objects, colors, faces, and human movement. The motorized Pan-Tilt HAT allows the camera to follow targets automatically, demonstrating how computer vision and motion control work together. Voice AI with the Fusion HAT+ The Fusion HAT+ simplifies hardware control through a unified Python library and supports safe Raspberry Pi shutdown. Its integrated microphone and speaker make it easy to develop voice-controlled assistants and other conversational AI applications. Compatible with Raspberry Pi 5, 4B, 3B+, 3B, and Zero 2 W Supports multiple cloud-based and local AI models Includes camera, Pan-Tilt HAT, 10DOF module, microphone, and speaker Projects covering voice AI, computer vision, sensors, and electronics Video lessons, documentation, and sample code Book: Physical AI with Raspberry Pi Using the Raspberry Pi and the AI Fusion Lab Kit, this book takes you step by step from the fundamentals of hardware interfacing to the development of intelligent systems capable of seeing, listening, speaking, and making decisions. Whether you are a student, educator, maker, or professional engineer, you will gain valuable experience through projects designed to build both knowledge and confidence. Beginning with system setup, GPIO programming, sensors, displays, motors, and automation techniques, the book gradually introduces more advanced topics, including speech recognition, text-to-speech synthesis, conversational AI, object recognition, and machine learning. Along the way, you will learn how to create voice-controlled devices, intelligent assistants, camera tracking systems, environmental monitoring solutions, and AI-powered embedded applications. Explore modern technologies such as OpenAI services, Ollama local large language models, OpenCV, MediaPipe, and YOLO object detection while gaining practical experience with real-world applications used in robotics, industrial automation, smart devices, and autonomous systems. You’ll discover how intelligent software can interact with sensors, cameras, motors, and displays to create systems that respond naturally to the world around them. Rather than simply following code examples, you will be encouraged to experiment, customize, and expand every project. The techniques and skills developed throughout this book provide a solid foundation for future innovation, rapid prototyping, research, and product development. If you are ready to move beyond traditional electronics and explore the future of intelligent embedded systems, this book will guide you every step of the way. This bundle contains: SunFounder AI Fusion Lab Kit for Raspberry Pi (normal price: €100) Book: Physical AI with Raspberry Pi (normal price: €45) Not included Raspberry Pi

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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Enhance your Raspberry Pi 5 with the Pironman 5, built with sturdy aluminum, superior cooling, NVMe M.2 SSD support, OLED display, RGB lighting, standard HDMI ports x2, and a secure power switch. It is perfect for NAS, Home Assistant, Media and Game Centers. The Pironman 5 is not just a case; it’s an upgrade that transforms your Raspberry Pi 5 into a powerful, efficient, and stylish device. The Pironman 5 includes the Pi 5 NVMe PIP (PCIe Peripheral Board), a PCIe adapter board specifically designed for NVMe solid-state drives. This board supports four sizes of NVMe SSDs: 2230, 2242, 2260, and 2280, all of which can be installed in an M.2 M key slot. The connection is certified for Gen 2.0 speeds (5 GT/sec), but can be forced to Gen 3.0 (10 GT/sec) for faster performance. Expandable NVMe M.2 SSD Slot Boost your Raspberry Pi 5's performance with the Pironman 5's NVMe M.2 SSD slot, supporting multiple sizes (2230, 2242, 2260, 2280) for increased storage and faster system response. Advanced Cooling System Keep your Raspberry Pi 5 cool and stylish with the Pironman 5's tower cooler and dual RGB fans, featuring dust filters for durable, low-maintenance operation. OLED Display for Instant Insights The Pironman 5 includes a 0.96" OLED display, providing immediate updates on CPU and RAM usage, temperature, IP address, and more. Enhanced Functionality and Safety The Pironman 5 secures your Raspberry Pi 5 with features like safe shutdown, customizable RGB LEDs, HDMI ports, an IR receiver, and an external GPIO extender, enhancing functionality and connectivity. Features Raspberry Pi 5 mini PC 0.96" OLED Display showing Raspberry Pi’s CPU usage, temperature, disk usage, IP address, RAM usage etc. Tower cooler can cool a 100% CPU load Pi to 39°C at 25°C room temperature 2 RGB Fans, with GPIO control 1 PWM Fan on the Tower Cooler is controlled by the Raspberry Pi system. Supports four (PCIe Gen 2.0 / PCIe Gen 3.0) NVMe M.2 SSD sizes: 2230, 2242, 2260, and 2280. 4 WS2812 Addressable RGB LED light up the whole case with cool light effect IR Receiver for multi-media center like Kodi or Volumio Retro metal power button for safe shut down External GPIO extender with pin name label, for easy access Equipped with a spring-loaded socket for easy card removal Aluminum main body with clear Acrylic side panel Features two standard HDMI ports Downloads Documentation

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A Beginner's Guide to AI and Edge Computing Artificial Intelligence (AI) is now part of our daily lives. With companies developing low-cost AI-powered hardware into their products, it is now becoming a reality to purchase AI accelerator hardware at comparatively very low costs. One such hardware accelerator is the Hailo module which is fully compatible with the Raspberry Pi 5. The Raspberry Pi AI Kit is a cleverly designed hardware as it bundles an M.2-based Hailo-8L accelerator with the Raspberry Pi M.2 HAT+ to offer high speed inferencing on the Raspberry Pi 5. Using the Raspberry Pi AI Kit, you can build complex AI-based vision applications, running in real-time, such as object detection, pose estimation, instance segmentation, home automation, security, robotics, and many more neural network-based applications. This book is an introduction to the Raspberry Pi AI Kit, and it is aimed to provide some help to readers who are new to the kit and wanting to run some simple AI-based visual models on their Raspberry Pi 5 computers. The book is not meant to cover the detailed process of model creation and compilation, which is done on an Ubuntu computer with massive disk space and 32 GB memory. Examples of pre-trained and custom object detection are given in the book. Two fully tested and working projects are given in the book. The first project explains how a person can be detected and how an LED can be activated after the detection, and how the detection can be acknowledged by pressing an external button. The second project illustrates how a person can be detected, and how this information can be passed to a smart phone over a Wi-Fi link, as well as how the detection can be acknowledged by sending a message from the smartphone to your Raspberry Pi 5.

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Program and Build Raspberry Pi 5 Based Ham Station Utilities with the RTL-SDR The RTL-SDR devices (V3 and V4) have gained popularity among radio amateurs because of their very low cost and rich features. A basic system may consist of a USB based RTL-SDR device (dongle) with a suitable antenna, a Raspberry Pi 5 computer, a USB based external audio input-output adapter, and software installed on the Raspberry Pi 5 computer. With such a modest setup, it is possible to receive signals from around 24 MHz to over 1.7 GHz. This book is aimed at amateur radio enthusiasts and electronic engineering students, as well as at anyone interested in learning to use the Raspberry Pi 5 to build electronic projects. The book is suitable for both beginners through experienced readers. Some knowledge of the Python programming language is required to understand and eventually modify the projects given in the book. A block diagram, a circuit diagram, and a complete Python program listing is given for each project, alongside a comprehensive description. The following popular RTL-SDR programs are discussed in detail, aided by step-by-step installation guides for practical use on a Raspberry Pi 5: SimpleFM GQRX SDR++ CubicSDR RTL-SDR Server Dump1090 FLDIGI Quick RTL_433 aldo xcwcp GPredict TWCLOCK CQRLOG klog Morse2Ascii PyQSO Welle.io Ham Clock CHIRP xastir qsstv flrig XyGrib FreeDV Qtel (EchoLink) XDX (DX-Cluster) WSJT-X The application of the Python programming language on the latest Raspberry Pi 5 platform precludes the use of the programs in the book from working on older versions of Raspberry Pi computers.

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Raspberry Pi-based Eye Catcher A standard sand clock just shows how time passes. In contrast, this Raspberry Pi Pico-controlled sand clock shows the exact time by “engraving” the four digits for hour and minute into the layer of sand. After an adjustable time the sand is flattened out by two vibration motors and everything begins all over again. At the heart of the sand clock are two servo motors driving a writing pen through a pantograph mechanism. A third servo motor lifts the pen up and down. The sand container is equipped with two vibration motors to flatten the sand. The electronic part of the sand clock consists of a Raspberry Pi Pico and an RTC/driver board with a real-time clock, plus driver circuits for the servo motors. A detailed construction manual is available for downloading. Features Dimensions: 135 x 110 x 80 mm Build time: approx. 1.5 to 2 hours Included 3x Precut acrylic sheets with all mechanical parts 3x Mini servo motors 2x Vibration motors 1x Raspberry Pi Pico 1x RTC/driver board with assembled parts Nuts, bolts, spacers, and wires for the assembly Fine-grained white sand

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Comprehensive Book-Hardware Bundle for the RP2040 Microcontroller with over 80 Projects Unlock the potential of modern controller technology with the Raspberry Pi Pico in this bundle. Perfect for both beginners and experienced users, the easy-to-follow guide takes you from the basics of electronics to the complexities of digital signal processing. With the Raspberry Pi Pico, the dedicated hardware kit and MicroPython programming, you will learn the key principles of circuit design, data collection, and processing. Get hands-on with over 80 projects like a stopwatch with an OLED display, a laser distance meter, and a servo-controlled fan. These projects are designed to help you apply what you've learned in real-world scenarios. The book also covers advanced topics like wireless RFID technology, object detection, and sensor integration for robotics. Whether you're looking to build your skills in electronics or dive deeper into embedded systems, this bundle is the perfect resource to help you explore the full potential of the Raspberry Pi Pico. Contents of the Bundle 1x Project Book (273 pages) 1x Smart Car Kit Electronic Parts 2x Solderless breadboard (400 holes) 1x Solderless breadboard (170 holes) 5x Colorful 5 mm LEDs (green, red, blue, yellow and white) 1x Laser transmitter 1x Passive buzzer 1x Micro USB cable (30 cm) 1x 65 Jumper wires 1x 20 cm male to female Dupont wire 1x Clear case 1x Magnet (diameter: 8 mm, thickness: 5 mm) 1x Rotary potentiometer 10x 2 KΩ resistors 2x M2.5x30 mm copper pillars 10x Phillips pan head screws 10x M2.5 nickel hex nuts 1x 2-inch dual-purpose screwdriver Modules 1x RGB module 1x 9G servo 1x Dual-axis XY joystick module 1x RC522 RFID module 1x 4 Bits digital LED display module 1x Traffic light display module 1x Rotary Encoder module 1x 1602 LCD Display module (Blue) 1x Photoresistor module 1x DC motor with male Dupont wire 1x Fan blade 1x Raindrops module 1x OLED module 1x Membrane switch keyboard 1x Mini magnetic spring module 1x Infrared remote control 1x Infrared receiver module 1x DC stepper motor driver board 1x Button Sensors 1x Vibration sensor 1x Soil moisture sensor 1x Sound sensor 1x Mini PIR motion sensor 1x Temperature & Humidity sensor 1x Flame sensor 2x Crash sensor 2x Tracking sensor 1x Ultrasonic sensor

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Specifications Dual ARM Cortex-M0+ @ 133 MHz 264 kB on-chip SRAM in six independent banks Support for up to 16 MB of off-chip Flash memory via dedicated QSPI bus DMA controller Fully-connected AHB crossbar Interpolator and integer divider peripherals On-chip programmable LDO to generate core voltage 2x on-chip PLLs to generate USB and core clocks 30x GPIO pins, 4 of which can be used as analogue inputs Peripherals 2x UARTs 2x SPI controllers 2x I²C controllers 16x PWM channels USB 1.1 controller and PHY, with host and device support 8x PIO state machines What you'll get 10x bare RP2040 chips

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