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This collection features the best of Elektor Magazine's articles on embedded systems and artificial intelligence. From hands-on programming guides to innovative AI experiments, these pieces offer valuable insights and practical knowledge for engineers, developers, and enthusiasts exploring the evolving intersection of hardware design, software innovation, and intelligent technology. Contents Programming PICs from the Ground UpAssembler routine to output a sine wave Object-Oriented ProgrammingA Short Primer Using C++ Programming an FPGA Tracking Down Microcontroller Buffer Overflows with 0xDEADBEEF Too Quick to Code and Too Slow to Test? Understanding the Neurons in Neural NetworksEmbedded Neurons MAUI Programming for PC, Tablet, and SmartphoneThe New Framework in Theory and Practice USB Killer DetectorBetter Safe Than Sorry Understanding the Neurons in Neural NetworksArtificial Neurons A Bare-Metal Programming Guide Part 1: For STM32 and Other Controllers Part 2: Accurate Timing, the UART, and Debugging Part 3: CMSIS Headers, Automatic Testing, and a Web Server Introduction to TinyMLBig Is Not Always Better Microprocessors for Embedded SystemsPeculiar Parts, the Series FPGAs for BeginnersThe Path From MCU to FPGA Programming AI in Electronics DevelopmentAn Update After Only One Year AI in the Electronics LabGoogle Bard and Flux Copilot Put to the Test ESP32 and ChatGPTOn the Way to a Self-Programming System… Audio DSP FX Processor Board Part 1: Features and Design Part 2: Creating Applications Rust + EmbeddedA Development Power Duo A Smart Object CounterImage Recognition Made Easy with Edge Impulse Universal Garden LoggerA Step Towards AI Gardening A VHDL ClockMade with ChatGPT TensorFlow Lite on Small MicrocontrollersA (Very) Beginner’s Point of View Mosquito DetectionUsing Open Datasets and Arduino Nicla Vision Artificial Intelligence Timeline Intro to AI AlgorithmsPrompt: Which Algorithms Implement Each AI Tool? Bringing AI to the Edgewith ESP32-P4 The Growing Role of Edge AIA Trend Shaping the Future

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ARM Cortex-M Embedded Design from 0 to 1 Hobbyists can mash together amazing functional systems using platforms like Arduino or Raspberry Pi, but it is imperative that engineers and product designers understand the foundational knowledge of embedded design. There are very few resources available that describe the thinking, strategies, and processes to take an idea through hardware design and low-level driver development, and successfully build a complete embedded system. Many engineers end up learning the hard way, or never really learn at all. ARM processors are essentially ubiquitous in embedded systems. Design engineers building novel devices must understand the fundamentals of these systems and be able to break down large, complicated ideas into manageable pieces. Successful product development means traversing a huge amount of documentation to understand how to accomplish what you need, then put everything together to create a robust system that will reliably operate and be maintainable for years to come. This book is a case study in embedded design including discussion of the hardware, processor initialization, low‑level driver development, and application interface design for a product. Though we describe this through a specific application of a Cortex-M3 development board, our mission is to help the reader build foundational skills critical to being an excellent product developer. The completed development board is available to maximize the impact of this book, and the working platform that you create can then be used as a base for further development and learning. The Embedded in Embedded program is about teaching fundamental skill sets to help engineers build a solid foundation of knowledge that can be applied in any design environment. With nearly 20 years of experience in the industry, the author communicates the critical skill development that is demanded by companies and essential to successful design. This book is as much about building a great design process, critical thinking, and even social considerations important to developers as it is about technical hardware and firmware design. Downloads EiE Software Archive (200 MB) IAR ARM 8.10.1 (Recommended IDE version to use) (1.2 GB) IAR ARM 7.20.1 (Optional IDE version to use) (600 MB)

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History and Future in the Internet of Things This book thoroughly reviews the history of the development of embedded Operating Systems, covers the technical characteristics, historic facts, as well as background business stories of mainstream embedded Operating Systems, and analyzes the technical evolution, market development, and new opportunities of embedded Operating Systems in the age of the Internet of Things. From the perspective of time, the book examines the evolution of critical technical aspects, including real-time and Power Management of embedded Operating Systems and Linux, Internet of Things security, communication, and cloud computing. The book looks into applications of embedded Operating Systems with important markets of mobile phones, communication equipment, automobile, and wearable devices, and also discusses business model and the issue of intellectual property of embedded Operating Systems. In addition, the book walks through the status quo, technical features, product evaluation and background of the Internet of Things Operating Systems in the second half of the book.

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Technology is constantly changing. New microcontrollers become available every year and old ones become redundant. The one thing that has stayed the same is the C programming language used to program these microcontrollers. If you would like to learn this standard language to program microcontrollers, then this book is for you! ARM microcontrollers are available from a large number of manufacturers. They are 32-bit microcontrollers and usually contain a decent amount of memory and a large number of on-chip peripherals. Although this book concentrates on ARM microcontrollers from Atmel, the C programming language applies equally to other manufacturer’s ARMs as well as other microcontrollers. Features of this book Use only free or open source software. Learn how to download, set up and use free C programming tools. Start learning the C language to write simple PC programs before tackling embedded programming - no need to buy an embedded system right away! Start learning to program from the very first chapter with simple programs and slowly build from there. No programming experience is necessary! Learn by doing - type and run the example programs and exercises. Sample programs and exercises can be downloaded from the Internet. A fun way to learn the C programming language. Ideal for electronic hobbyists, students and engineers wanting to learn the C programming language in an embedded environment on ARM microcontrollers.

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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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A Practical Guide to AI, Python, and Hardware Projects Welcome to your BeagleY-AI journey! This compact, powerful, and affordable single-board computer is perfect for developers and hobbyists. With its dedicated 4 TOPS AI co-processor and a 1.4 GHz Quad-core Cortex-A53 CPU, the BeagleY-AI is equipped to handle both AI applications and real-time I/O tasks. Powered by the Texas Instruments AM67A processor, it offers DSPs, a 3D graphics unit, and video accelerators. Inside this handbook, you‘ll find over 50 hands-on projects that cover a wide range of topics—from basic circuits with LEDs and sensors to an AI-driven project. Each project is written in Python 3 and includes detailed explanations and full program listings to guide you. Whether you‘re a beginner or more advanced, you can follow these projects as they are or modify them to fit your own creative ideas. Here’s a glimpse of some exciting projects included in this handbook: Morse Code Exerciser with LED or BuzzerType a message and watch it come to life as an LED or buzzer translates your text into Morse code. Ultrasonic Distance MeasurementUse an ultrasonic sensor to measure distances and display the result in real time. Environmental Data Display & VisualizationCollect temperature, pressure, and humidity readings from the BME280 sensor, and display or plot them on a graphical interface. SPI – Voltmeter with ADCLearn how to measure voltage using an external ADC and display the results on your BeagleY-AI. GPS Coordinates DisplayTrack your location with a GPS module and view geographic coordinates on your screen. BeagleY-AI and Raspberry Pi 4 CommunicationDiscover how to make your BeagleY-AI and Raspberry Pi communicate over a serial link and exchange data. AI-Driven Object Detection with TensorFlow LiteSet up and run an object detection model using TensorFlow Lite on the BeagleY-AI platform, with complete hardware and software details provided.

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Learn to Build Intelligent Embedded Systems Build smarter embedded systems with Arduino UNO Q. This book gives you the tools, knowledge, and confidence to turn ideas into intelligent, working solutions using the Arduino UNO Q platform. Discover how to build intelligent embedded systems with the Arduino UNO Q and AI. Unlock the full potential of the Arduino UNO Q, a next-generation platform that combines the real-time power of the STM32U585 microcontroller with the flexibility of a Qualcomm Dragonwing QRB2210 microprocessor. Learn how to rapidly prototype real-world applications using the Arduino IDE for low-level embedded control and Python in Arduino App Lab for high-level development. Build confidence through hands-on projects that guide you step by step from basic board features to complete working systems. Explore ready-to-use, AI based Arduino App Lab examples and see how they can jump-start your development and reduce time to deployment. Step into the world of Edge AI with a clear, practical introduction to Edge Impulse Studio—no prior AI experience required. Follow a complete, real-world workflow to create a Keyword Spotting AI application, covering data collection, model training, optimization, and on-device inference using the Edge Impulse Studio. Bridge the gap between embedded systems and machine learning and learn how to bring intelligence directly onto your hardware. Perfect for embedded engineers, educators, students, and makers looking to stay ahead in AI-enabled product development.

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This book is all about building your own DIY home control system. It presents two innovative ways to assemble such a system: By recycling old PC hardware – possibly extending the life of an old PC, or by using Raspberry Pi. In both cases, the main system outlined in this book will consist of a computer platform, a wireless mains outlet, a controller and a USB webcam – All linked together by Linux. By using the Raspberry Pi in conjunction with Arduino (used as an advanced I/O system board), it is possible to construct a small, compact, embedded control system offering enhanced capacity for USB integration, webcams, thermal monitoring and communication with the outside world. The experience required to undertake the projects within this book are minimal exposure to PC hardware and software, the ability to surf the internet, burn a CD-ROM and assemble a small PCB.

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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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Build Smart Applications with Raspberry Pi, Arduino, and ESP32 Discover how easy and exciting mobile app development can be with MIT App Inventor. This hands-on guide takes you from basic concepts to building real-world mobile applications using a simple visual programming approach—no prior coding experience required. You will create IoT and AI-powered apps for Android devices and explore how App Inventor can also be used with iPhones and iPads. Connect your applications to platforms such as Arduino UNO R4 WiFi, ESP32, Raspberry Pi Pico (2)W and Raspberry Pi 5, enabling you to build smart, connected systems. Inside the book, you will learn how to: Build interactive apps using buttons, images, sound, and multimedia Create text-to-speech and speech-recognition applications Develop camera-based and location-aware (GPS) apps Design useful tools such as calculators and educational apps Work with smartphone sensors like accelerometers and light sensors Build AI-powered applications, including voice assistants and image-generation features Send and receive messages, and create communication-based apps Connect mobile apps to hardware using Wi-Fi and Bluetooth Control real devices such as LEDs, motors, and sensors Designed for beginners, students, and hobbyists, this book focuses on learning by doing. By the end, you will have the skills and confidence to create your own innovative applications that interact with both the digital and physical worlds. Start building and turning your ideas into reality.

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Learn to Build Intelligent Embedded Systems Build smarter embedded systems with Arduino UNO Q. This book gives you the tools, knowledge, and confidence to turn ideas into intelligent, working solutions using the Arduino UNO Q platform. Discover how to build intelligent embedded systems with the Arduino UNO Q and AI. Unlock the full potential of the Arduino UNO Q, a next-generation platform that combines the real-time power of the STM32U585 microcontroller with the flexibility of a Qualcomm Dragonwing QRB2210 microprocessor. Learn how to rapidly prototype real-world applications using the Arduino IDE for low-level embedded control and Python in Arduino App Lab for high-level development. Build confidence through hands-on projects that guide you step by step from basic board features to complete working systems. Explore ready-to-use, AI based Arduino App Lab examples and see how they can jump-start your development and reduce time to deployment. Step into the world of Edge AI with a clear, practical introduction to Edge Impulse Studio—no prior AI experience required. Follow a complete, real-world workflow to create a Keyword Spotting AI application, covering data collection, model training, optimization, and on-device inference using the Edge Impulse Studio. Bridge the gap between embedded systems and machine learning and learn how to bring intelligence directly onto your hardware. Perfect for embedded engineers, educators, students, and makers looking to stay ahead in AI-enabled product development.

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A Practical Guide to AI, Python, and Hardware Projects Welcome to your BeagleY-AI journey! This compact, powerful, and affordable single-board computer is perfect for developers and hobbyists. With its dedicated 4 TOPS AI co-processor and a 1.4 GHz Quad-core Cortex-A53 CPU, the BeagleY-AI is equipped to handle both AI applications and real-time I/O tasks. Powered by the Texas Instruments AM67A processor, it offers DSPs, a 3D graphics unit, and video accelerators. Inside this handbook, you‘ll find over 50 hands-on projects that cover a wide range of topics—from basic circuits with LEDs and sensors to an AI-driven project. Each project is written in Python 3 and includes detailed explanations and full program listings to guide you. Whether you‘re a beginner or more advanced, you can follow these projects as they are or modify them to fit your own creative ideas. Here’s a glimpse of some exciting projects included in this handbook: Morse Code Exerciser with LED or BuzzerType a message and watch it come to life as an LED or buzzer translates your text into Morse code. Ultrasonic Distance MeasurementUse an ultrasonic sensor to measure distances and display the result in real time. Environmental Data Display & VisualizationCollect temperature, pressure, and humidity readings from the BME280 sensor, and display or plot them on a graphical interface. SPI – Voltmeter with ADCLearn how to measure voltage using an external ADC and display the results on your BeagleY-AI. GPS Coordinates DisplayTrack your location with a GPS module and view geographic coordinates on your screen. BeagleY-AI and Raspberry Pi 4 CommunicationDiscover how to make your BeagleY-AI and Raspberry Pi communicate over a serial link and exchange data. AI-Driven Object Detection with TensorFlow LiteSet up and run an object detection model using TensorFlow Lite on the BeagleY-AI platform, with complete hardware and software details provided.

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