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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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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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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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Arduino-compatible, ESP32-controlled, 2-wheeled Balancing Robot The Elektor Mini-Wheelie is an experimental autonomous self-balancing robot platform. Based on an ESP32-S3 microcontroller, the self-balancing robot is fully programmable using the Arduino environment and open-source libraries. Its wireless capabilities allow it to be controlled remotely over Wi-Fi, Bluetooth or ESP-NOW or to communicate with a user or even another robot. An ultrasonic transducer is available for detecting obstacles. Its color display can be used for displaying cute facial expressions or, for the more down-to-earth users, cryptic debug messages. The robot comes as a neat kit of parts that you must assemble yourself. Everything is included, even a screwdriver. Note: The Mini-Wheelie is an educational development platform intended for learning, experimentation, and robotics development. It is not classified as a toy for children, and its features, documentation, and intended audience reflect this purpose. The product is aimed at students, educators, and developers who wish to explore robotics, programming, and hardware integration in an educational setting. Specifications ESP32-S3 microcontroller with Wi-Fi and Bluetooth MPU6050 6-axis Inertial Measurement Unit (IMU) Two independently controlled 12 V electric motors with tachometer Ultrasonic transducer 2.9" TFT color display (320 x 240) MicroSD card slot Battery power monitor 3S rechargeable Li-Po battery (11.1 V/2200 mAh) Battery charger included Arduino-based open-source software Dimensions (W x L x H): 23 x 8 x 13 cm Included 1x ESP32-S3 Mainboard + MPU6050 module 1x LCD board (2.9 inch) 1x Ultrasonic sensor 1x Battery pack (2200 mAh) 1x Battery charger 1x Motor tyre kit 1x Case board 1x Acrylic board 1x Screwdriver 1x Protective strip 1x Flex cable B (8 cm) 1x Flex cable A (12 cm) 1x Flex cable C 4x Copper column A (25 mm) 4x Copper column B (55 mm) 4x Copper column C (5 mm) 2x Plastic nylon column 8x Screws A (10 mm) 24x Screws B (M3x5) 8x Nuts 24x Metal washers 2x Zip tie 1x MicroSD card (32 GB) 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, build, and master over 60 projects with Python The Raspberry Pi 5 is the latest single-board computer from the Raspberry Pi Foundation. It can be used in many applications, such as in audio and video media centers, as a desktop computer, in industrial controllers, robotics, and in many domestic and commercial applications. In addition to the well-established features found in other Raspberry Pi computers, the Raspberry Pi 5 offers Wi-Fi and Bluetooth (classic and BLE), which makes it a perfect match for IoT as well as in remote and Internet-based control and monitoring applications. It is now possible to develop many real-time projects such as audio digital signal processing, real-time digital filtering, real-time digital control and monitoring, and many other real-time operations using this tiny powerhouse. The book starts with an introduction to the Raspberry Pi 5 computer and covers the important topics of accessing the computer locally and remotely. Use of the console language commands as well as accessing and using the desktop GUI are described with working examples. The remaining parts of the book cover many Raspberry Pi 5-based hardware projects using components and devices such as LEDs and buzzers LCDs Ultrasonic sensors Temperature and atmospheric pressure sensors The Sense HAT Camera modules Example projects are given using Wi-Fi and Bluetooth modules to send and receive data from smartphones and PCs, and sending real-time temperature and atmospheric pressure data to the cloud. All projects given in the book have been fully tested for correct operation. Only basic programming and electronics experience are required to follow the projects. Brief descriptions, block diagrams, detailed circuit diagrams, and full Python program listings are given for all projects described.

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Vom Messwert zur stabilen Entscheidung Wie wird aus einem einfachen Mikrocontroller ein intelligentes System, das Sensorwerte erfasst, verarbeitet und sinnvoll darauf reagiert? Dieses Buch zeigt es Ihnen Schritt für Schritt – verständlich, praxisnah und ohne unnötige Vorkenntnisse. Sie beginnen mit den Grundlagen der digitalen und analogen Ein- und Ausgänge. Anschließend lernen Sie, wie Sensorwerte gelesen, geglättet und zuverlässig bewertet werden. Anschauliche Beispiele erklären, warum einzelne Messwerte oft täuschen können und wie Mittelwertbildung, Hysterese und einfache Entscheidungsregeln für stabile Ergebnisse sorgen. Nach und nach erweitern Sie Ihre Projekte um Displays, I²C-Kommunikation und mehrere vernetzte Mikrocontroller. So entstehen verteilte Systeme, in denen Raspberry Pi Pico und ATtiny-Controller Daten austauschen und gemeinsam Aufgaben übernehmen. Im fortgeschrittenen Teil erhalten Sie einen leicht verständlichen Einstieg in Merkmalsbildung, Datenvorverarbeitung, hybride Entscheidungsmodelle und TinyML-nahe Anwendungen. Dabei verbinden Sie klassische Regelungstechnik mit modernen datenbasierten Methoden. Alle Projekte werden von ausführlich kommentierten Programmen in C und MicroPython begleitet. Das Buch richtet sich an Einsteiger, Maker, Studierende und alle, die Embedded-Systeme von Grund auf verstehen möchten. Am Ende können Sie eigene Systeme entwickeln, die nicht nur messen, sondern Informationen auswerten, zuverlässige Entscheidungen treffen und gezielt reagieren.

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AI in Practice Dive into the fascinating world of robotics and automation! This Elektor Special shows you how to build your own robots with creativity, a little know-how, and affordable technology. From your first DIY project with Arduino or Raspberry Pi to intelligent systems with AI – this issue makes modern robotics understandable and accessible. Discover practical instructions, inspiring projects, and exciting insights into the maker scene. Learn how experimentation, community, and openness give rise to true innovation – and why robotics is so much more than just a technical hobby. Contents Imagination turns into reality Arduino-controlled Drawing Robot GalaxyRVR Mars Rover Kit for Arduino YDLIDAR X4Pro Lidar xHuskyLens AI Camera DOF Robot Arm with Raspberry Pi Pico Manufacturing Robots with Fischertechnik Pneumatic Industrial Robot Why Do We Keep Building Robot Dogs? Elektor Mini-Wheelie Robot Vehicles and Autonomous Driving

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TurtleBot 4 is the next-generation of the world’s most popular open source robotics platform for education and research, offering better computing power, better sensors and a world class user experience at an affordable price point.TurtleBot 4 Lite is equipped with an iRobot Create 3 mobile base, a powerful Raspberry Pi 4 running ROS 2, OAK-D spatial AI stereo camera, 2D LiDAR and more. All components have been seamlessly integrated to deliver an out-of-the-box development and learning platform.Specifications Base platform iRobot Create 3 Wheels (Diameter) 72 mm Ground Clearance 4.5 mm On-board Computer Raspberry Pi 4 (4 GB) Maximum linear velocity 0.31 m/s in safe mode0.46 m/s without safe mode Maximum angular velocity 1.90 rad/s Maximum payload 9 kg Operation time 2h 30m – 4h depending on load Charging time 2h 30m Lidar RPLIDAR A1M8 Camera OAK-D-Lite User Power VBAT @1.9 A5 V @ Low current3.3 V @ Low current USB Expansion 2x USB 2.0 (Type A)2x USB 3.0 (Type A) Programmable LEDs Create 3 Lightring Buttons and Switches 2x Create 3 User buttons1x Create 3 Power Button Battery 26 Wh Lithium Ion (14.4 V nominal) Charging Dock Included Size (L x W x H) 342 x 339 x 192 mm Weight 3.3 kg DownloadsUser Manual

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Le téléchargement intégral de ce numéro est disponible pour nos membres GOLD et GREEN sur le site Elektor Magazine ! Pas encore membre ? Cliquez ici. le Raspberry Pi 5une grande amélioration par rapport à son prédécesseur l'IA dans les laboratoires d'électroniqueBard de Google et Flux Copilot mis en test Générateur de formes d'ondes Arduino NanoNano + Code = Générateur de fonctions guirlande de Noël solaire détecteur de clé USB KillerMieux vaut prévenir que guérir un boîtier simple créé par fraiseuse à commande numérique (CNC)avec Autodesk Fusion 360 en utilisation personnelle production de cartes à faible quantitéavec et sans assemblage simulation IdO simplifiée avec Wokwile développeur Uri Shaked parle de design, de logiciels et d'autres choses encore guide de programmation Bare-Metal (3)en-têtes CMSIS, tests automatiques et serveur web LoRa, un couteau suisse (1)le matériel et le logiciel conception et construction de microphones MEMS outils à tester avant de souderoutils de simulation et de modélisation 3D gratuits nouveaux outils de Microchip!PICkit 5 et MPLAB ICD 5 sont disponibles maintenant ! prototypage rapide d'électronique souple et extensiblecomment la Voltera NOVA accélère l'innovation dans les systèmes électroniques portables isolation galvaniqueutilisation d?optocouplers à phototransistor la solution complexe ou la solution Anybus ?un Ethernet industriel embarqué réalisé en deux jours plutôt qu'en plusieurs mois votre liste de contrôle DFM essentielle filaments pour l?impression 3Dtypes, caractéristiques et utilisation dans le prototypage spécialistes pour une analyse efficace des signaux des bandes ELF à EHFles derniers analyseurs de spectre en temps réel de la série SPECTRAN® V6 d?Aaronia défis de l'analyse DFM pour les circuits flexibles et flexibles-rigides définir une ligne SMT infographie : prototypage et production révolutionner le secteur de l?industriel'essor des robots mobiles autonomes (AMR) prêt à relever encore plus de défisRohde & Schwarz étoffe sa famille d?oscilloscopes nouvelle génération avec le modèle 8 voies de la gamme R&S MXO 5 démarrer en électronique?Amplifying Differences mini plaque de refusion'pour l'assemblage ou la réparation de petits circuits CMS ne commencez pas avec un prototype, mais plutôt avec un « pretotype » !vérifiez qu'il existe un marché pour votre produit avant d'allumer votre fer à souder 2023 : l'Odyssée de l'IAassistance à la conception d'un projet matériel Bruxelles et l?innovationsoutien aux technologies avancées

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Le téléchargement intégral de ce numéro est disponible pour nos membres GOLD et GREEN sur le site Elektor Magazine ! Pas encore membre ? Cliquez ici. programmation PIO sur le Raspberry Pi PicoNeuf instructions, de multiples possibilités l'IA en ligne de commandeDéveloppement, compilation et validation de projets embarqués depuis le terminal le Scrutiny DebuggerDéboguer, visualiser et tester du code C/C++ embarqué carte breakout Sigfox (1)Développement d’une BoB radio alimentation à faible bruit (2)Construction, assemblage et mise en œuvre pratique générateur de signaux simple basé sur le RP2040Signaux analogiques et numériques à la découverte du futur de la domotique avec Matter et l’IA EdgeLes dernières versions de Matter et l’essor de l’IA en périphérie de réseau (edge) donnent-ils enfin aux ingénieurs les outils nécessaires pour construire les maisons intelligentes et parfaitement intégrées promises aux utilisateurs ? capteurs de pression différentielleLa maintenance prédictive appliquée aux systèmes CVC la sécurité dès la conceptionPrincipes d’ingénierie pour limiter les défaillances la sécurité des systèmes embarqués n’est plus une option la CRA et la PQC redéfinissent les priorités de la sécurité embarquéePourquoi même les petites entreprises IoT et industrielles doivent prévoir une mise à niveau embedded world 2026Entretien avec Benedikt Weyerer, directeur d’embedded world prise en main du bus I3CUtilisation de matériel de ST et Microchip le projet BLEnkyPrototypage rapide d’applications Bluetooth Low Energy modulation de largeur d’impulsionDu thermostat tout ou rien à un signal analogique continu filtré audiotroniqueDes circuits audio agréables à l’écoute, à réaliser soi-même sur le vifLisez donc le manuel ! carte émetteur-récepteur audio ESP32 (4)Réglage des horloges et une option filaire 2026 : une odyssée de l’IAConséquences du vibe coding charge CC symétriqueCharge CC symétrique, statique ou dynamique comptage de visages avec MaixCAMUne méthode simple pour estimer la taille d’un public

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