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For Raspberry Pi, ESP32 and nRF52 with Python, Arduino and Zephyr Bluetooth Low Energy (BLE) radio chips are ubiquitous from Raspberry Pi to light bulbs. BLE is an elaborate technology with a comprehensive specification, but the basics are quite accessible. A progressive and systematic approach will lead you far in mastering this wireless communication technique, which is essential for working in low power scenarios. In this book, you’ll learn how to: Discover BLE devices in the neighborhood by listening to their advertisements. Create your own BLE devices advertising data. Connect to BLE devices such as heart rate monitors and proximity reporters. Create secure connections to BLE devices with encryption and authentication. Understand BLE service and profile specifications and implement them. Reverse engineer a BLE device with a proprietary implementation and control it with your own software. Make your BLE devices use as little power as possible. This book shows you the ropes of BLE programming with Python and the Bleak library on a Raspberry Pi or PC, with C++ and NimBLE-Arduino on Espressif’s ESP32 development boards, and with C on one of the development boards supported by the Zephyr real-time operating system, such as Nordic Semiconductor's nRF52 boards. Starting with a very little amount of theory, you’ll develop code right from the beginning. After you’ve completed this book, you’ll know enough to create your own BLE applications.

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Projects with Arduino Uno & Raspberry Pi with Examples for the MCP2515 CAN Bus Interface Module This book details the use of the Arduino Uno and the Raspberry Pi 4 in practical CAN bus based projects. Using either the Arduino Uno or the Raspberry Pi with off-the-shelf CAN bus interface modules considerably ease developing, debugging, and testing CAN bus based projects. This book is written for students, practicing engineers, enthusiasts, and for everyone else wanting to learn more about the CAN bus and its applications. The book assumes that the reader has some knowledge of basic electronics. Knowledge of the C and Python programming languages and programming the Arduino Uno using its IDE and Raspberry Pi will be useful, especially if the reader intends to develop microcontroller-based projects using the CAN bus. The book should be a useful source of reference material for anyone interested in finding answers to questions such as: What bus systems are available for the automotive industry? What are the principles of the CAN bus? How can I create a physical CAN bus? What types of frames (or data packets) are available in a CAN bus system? How can errors be detected in a CAN bus system and how dependable is a CAN bus system? What types of CAN bus controllers exist? How do I use the MCP2515 CAN bus controller? How do I create 2-node Arduino Uno-based CAN bus projects? How do I create 3-node Arduino Uno-based CAN bus projects? How do I set the acceptance masks and acceptance filters? How do I analyze data on the CAN bus? How do I create 2-node Raspberry Pi-based CAN bus projects? How do I create 3-node Raspberry Pi-based CAN bus projects?

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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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Multitasking and multiprocessing have become a very important topic in microcontroller-based systems, namely in complex commercial, domestic, and industrial automation applications. As the complexity of projects grows, more functionalities are demanded from the projects. Such projects require the use of multiple inter-related tasks running on the same system and sharing the available resources, such as the CPU, memory, and input-output ports. As a result of this, the importance of multitasking operations in microcontroller-based applications has grown steadily over the last few years. Many complex automation projects now make use of some form of a multitasking kernel. This book is project-based and its main aim is to teach the basic features of multitasking using the Python 3 programming language on Raspberry Pi. Many fully tested projects are provided in the book using the multitasking modules of Python. Each project is described fully and in detail. Complete program listings are given for each project. Readers should be able to use the projects as they are, or modify them to suit their own needs. The following Python multitasking modules have been described and used in the projects: Fork Thread Threading Subprocess Multiprocessing The book includes simple multitasking projects such as independently controlling multiple LEDs, to more complex multitasking projects such as on/off temperature control, traffic lights control, 2-digit, and 4-digit 7-segment LED event counter, reaction timer, stepper motor control, keypad based projects, car park controller, and many more. The fundamental multitasking concepts such as process synchronization, process communication, and memory sharing techniques have been described in projects concerning event flags, queues, semaphores, values, and so on.

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Develop innovative hardware-based projects in C The Raspberry Pi has traditionally been programmed using Python. Although this is a very powerful language, many programmers may not be familiar with it. C on the other hand is perhaps the most commonly used programming language and all embedded microcontrollers can be programmed using it. The C language is taught in most technical colleges and universities and almost all engineering students are familiar with using it with their projects. This book is about using the Raspberry Pi with C to develop a range of hardware-based projects. Two of the most popular C libraries, wiringPi and pigpio are used. The book starts with an introduction to C and most students and newcomers will find this chapter invaluable. Many projects are provided in the book, including using Wi-Fi and Bluetooth to establish communication with smartphones. Many sensor and hardware-based projects are included. Both wiringPi and pigpio libraries are used in all projects. Complete program listings are given with full explanations. All projects have been fully tested and work. The following hardware-based projects are provided in the book: Using sensors Using LCDs I²C and SPI buses Serial communication Multitasking External and timer interrupts Using Wi-Fi Webservers Communicating with smartphones Using Bluetooth Sending data to the cloud Program listings of all Raspberry Pi projects developed in this book are available on the Elektor website. Readers can download and use these programs in their projects. Alternatively, they can customize them to suit their applications.

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Projects with Thonny-IDE, uPyCraft-IDE, and ESP32 The 'Python' programming language has enjoyed an enormous upswing in recent years. Not least, various single-board systems such as the Raspberry Pi have contributed to its popularity. But Python has also found widespread use in other fields, such as artificial intelligence (AI) or machine learning (ML). It is obvious, therefore, to use Python or the 'MicroPython' variant for use in SoCs (Systems on Chip) as well. Powerful controllers such as the ESP32 from Espressif Systems offer excellent performance as well as Wi-Fi and Bluetooth functionality at an affordable price. With these features, the Maker scene has been taken by storm. Compared to other controllers, the ESP32 has a significantly larger flash and SRAM memory, as well as a much higher CPU speed. Due to these characteristics, the chip is not only suitable for classic C applications, but also for programming with MicroPython. This book introduces the application of modern one-chip systems. In addition to the technical background, the focus is on MicroPython itself. After the introduction to the language, the programming skills learned are immediately put into practice. The individual projects are suitable for use in the laboratory as well as for everyday applications. So, in addition to the actual learning effect, the focus is also on the joy of building complete and useful devices. By using laboratory breadboards, circuits of all kinds can be realized with little effort, turning the testing and debugging of the 100% homebrew projects into an instructive pleasure. The various applications, such as weather stations, digital voltmeters, ultrasound range finders, RFID card readers or function generators, make the projects presented ideally suited for practical courses or subject and study work in the natural sciences, or in science and technology classes.

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Zeitsteuerung, Scheduler, PIO und Zustandsmaschinen Multitasking ist der Schlüssel zu leistungsfähigen Embedded-Systemen, und zugleich eine der größten Herausforderungen in der Mikrocontroller-Programmierung. Dieses Buch zeigt Ihnen Schritt für Schritt, wie Sie von einem einfachen Ein-Task-Programm zu einem strukturierten, reaktionsfähigen und skalierbaren System gelangen. Dabei steht nicht nur das Wie, sondern vor allem das Warum im Mittelpunkt. Sie lernen: warum scheinbare Parallelität entsteht weshalb blockierende Programme instabil werden wie Aufgaben effizient und kontrolliert parallel ablaufen Ausgehend vom klassischen Superloop vermittelt das Buch moderne Multitasking-Strategien – von nicht-blockierender Programmierung und Tick-Systemen bis zu Task-Schedulern, Zustandsmaschinen und ereignisgesteuerten Konzepten. Der Fokus liegt auf der Praxis: Sensoren, Displays, Kommunikation und reale Anwendungen werden Schritt für Schritt integriert und mit verständlich kommentierten Beispielprogrammen erklärt. Fortgeschrittene Themen umfassen: Multicore-Programmierung mit dem Raspberry Pi Pico asynchrones Programmieren mit uasyncio RTOS-Grundlagen mit FreeRTOS die Kombination aus Multicore und RTOS Dabei werden auch die Grenzen dieser Techniken, insbesondere unter MicroPython, klar aufgezeigt. Das Buch richtet sich an ambitionierte Einsteiger und fortgeschrittene Entwickler, die Embedded-Systeme fundiert verstehen und robuste, wartbare Multitasking-Anwendungen entwickeln möchten.

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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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Réalisés par les créateurs du MagPi, le magazine officiel de Raspberry Pi Démarrez avec le Raspberry Pi 5, le dernier-né et le plus performant de la famille des nano-ordinateurs Raspberry Pi. Apprenez à coder et à réaliser des projets avec cet ordinateur étonnant. Dans ce manuel dédié au Raspberry Pi 5, nous vous proposons aussi de nombreuses idées de projets également réalisables avec le Raspberry Pi 4, le Raspberry Pi Zero 2 W et le Raspberry Pi Pico W. Avec des tutoriels, des projets pratiques, des essais techniques, des guides et bien plus encore, il s’agit de la ressource ultime pour le Raspberry Pi ! 228 pages sur le Raspberry Pi Tout ce que vous devez savoir sur le Raspberry Pi 5 Prise en main de tous les Raspberry Pi Amusez-vous et apprenez l’électronique avec le Pico W Des projets inspirants pour vous donner des idées de réalisations Apprenez μPython en construisant une mini-console Démarrez avec le module caméra Raspberry Pi Intelligence artificielle, codage de son propre agent ChatGP

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Modular and Scalable Control Systems Using Structured Text This book offers a structured and practical approach to modern PLC development using object-oriented principles. It is a guide for engineers, programmers, and students seeking to harness the power of object-oriented programming (OOP) in the context of industrial automation with PLCs. The content focuses on the CODESYS development environment and Structured Text (ST), both of which support modern programming techniques while maintaining compatibility with real-time automation requirements. Through step-by-step demos and instructional examples, it demonstrates how modular, reusable code can enhance development efficiency, simplify ongoing maintenance, and enable scalable and flexible control system architectures. Key topics include: Structured Text fundamentals: conditions, loops, arrays, and functions Object-oriented concepts: classes, methods, and inheritance Advanced techniques: polymorphism, interfaces, and access control Modular design with reusable components and structured program flow Implementation of finite state machines and scalable application design Built around instructional demos and clear explanations, this book helps readers develop maintainable and modern control software in the CODESYS environment using proven programming techniques.

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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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