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Diese Ausgabe steht allen GOLD- und GREEN-Mitgliedern auf der ElektorMagazine-Website zum Download bereit! Sie sind noch kein Mitglied? Hier klicken! Der ESP-BLASTEine Mini-Raketendrohne mit ESP32, die über 100 km/h erreicht Wireless Workshop (1)Freigeschaltetes Funkmodul: 433-MHz-CC1101-Sub-GHz-Transceiver AM-Sendermit Rechteck-/Sinuswellengenerator auf Raspberry Pi Pico STM32Cube Innovations ChallengeTreten Sie mit Ihrem besten STM32C5-Design an CoffeeCallerWie ein langer Flur zu einer maßgefertigten Mesh-Netzwerk-Platine führte AudiotronicsKlirrfaktor Elektor ist 65Projekte aus früheren September/Oktober-Ausgaben Geräteortung durch Bluetooth Channel SoundingZentimetergenaue Entfernungsmessung im IoT der nächsten Generation 2026: Eine KI-OdysseeQuantencomputing ist nicht die nächste GPU Cloud-Schutz durch Edge-Sicherheit Erste Erfahrungen mit dem HackRF ProPraktische Tests mit der neuen SDR-Hardware Herausforderung ElektromobilitätEffiziente Lötlösungen für moderne Fahrzeugtechnik Modem-Update von GPRS/2G auf LTE/4Gam Beispiel einer Funk-Alarmzentrale Loop-Antenne mit RF BricksTeil 1: Kurzwellen-Antenne mit einstellbarer Richtwirkung im Selbstbau Internetradio-zu-AM-KonverterVerwendung eines ESP32-S3 als Sender Projekt 2.0 mioty – ein ÜberblickLPWAN à la Fraunhofer Werkbank-WeisheitPraktische Tipps von Experten Walter, das kompakte IoT-ModulTeil 2: Zugriff auf Wetter- und Datendienste

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This complete ESP32 microcontroller programming course features a textbook, a component kit, hands-on projects, and a comprehensive online course with simulations. It is ideal for step-by-step learning of embedded systems programming in MicroPython using a practical, hands-on approach. A Practical Introduction to Embedded Systems with the ESP32 This course is designed for people who are new to embedded systems and looking for a structured, example-driven way to get started. A kit of parts comprising LEDs and resistors, switches, sensors and actuators, displays, a breadboard and wires, and more is included. These are used in the course to illustrate example applications. No prior experience with Arduino or embedded development is required. Each section features hands-on examples and mini projects designed to reinforce key concepts and inspire deeper exploration. By the end of the course, you’ll be able not only to reproduce the examples but also to build on them with your own ideas and applications. What Will You Learn? Microcontroller programming in MicroPython with the ESP32 using the Thonny IDE Working with Digital I/O, read buttons and encoders, control LEDs and relays Read analog inputs, voltages, and analog sensors Generating analog output signals and PWM Use serial communication like UART, I²C and SPI to control displays and read digital sensors and SD cards Managing time Working with interrupts Real-time sensor input and control via buttons, LEDs, and displays Control actuators like relays and servo motors Who Is It For? Students and self-learners exploring embedded systems Makers and IoT enthusiasts looking to improve their hardware skills Educators and trainers seeking ready-to-teach material What's Inside the Box? Access to the full course on the Elektor Academy Pro Learning Platform ESP32 microcontroller board + USB cable Book: Programming Microcontrollers in MicroPython Downloadable project files for every module Component Box: 2× LED, red, 5 mm LED, green, 5 mm 3× Resistor, 470 Ω, 0.25 W LDR Potentiometer, 10 kΩ, linear Pushbutton Rotary encoder module Relay module DHT22 Humidity & Temperature Sensor TM1637-compatible 4-digit 7-segment display MPU-6050 IMU with headers SSD1306-compatible I²C OLED display Micro SD card adapter with header Buzzer SG90 Micro Servo ILI9341-compatible SPI 240×320 TFT display 20× Jumper wires Breadboard All Programming Courses (and differences in content) Course Arduino Raspberry Pi Pico with Arduino C/C++ ESP32 with Arduino C/C++ Raspberry Pi Pico with MicroPython ESP32 with MicroPython Online Course Access to Arduino Course Access to Pico with Arduino C/C++ Course Access to ESP32 with Arduino C/C++ Course Access to Pico with MicroPython Course Access to ESP32 with MicroPython Course Board Uno R3 Raspberry Pi Pico ESP32 Raspberry Pi Pico ESP32 Book Programming Microcontrollers in C/C++ Using Arduino Programming Microcontrollers in C/C++ Using Arduino Programming Microcontrollers in C/C++ Using Arduino Programming Microcontrollers in MicroPython Programming Microcontrollers in MicroPython Kit 40-piece Component Box 40-piece Component Box 40-piece Component Box 40-piece Component Box 40-piece Component Box

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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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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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All-in-One AI Learning and Development Platform for Edge Intelligence This NVIDIA Jetson-based AI Starter Kit is a versatile platform for learning, development, and hands-on experimentation in Edge AI. Designed for use with the NVIDIA Jetson Orin Nano, the kit combines an 11.6-inch IPS display, an 8-megapixel pan-tilt camera, and an AI voice interaction system. It includes 30 functional modules and 38 carefully designed Python courses that progress from beginner to advanced level. The course content covers Python fundamentals, sensor technology, AI vision, and image recognition. With step-by-step practical exercises ranging from basic programming to real-world computer vision applications, this kit provides an ideal platform for students, makers, developers, and anyone looking to explore artificial intelligence and edge computing. Please note: The NVIDIA Jetson Orin Nano is not included. Features Designed for the NVIDIA Jetson Orin Nano AI voice interaction module 8 MP camera with pan-tilt control Supports object and face tracking No soldering or complex wiring required Built-in 11.6-inch IPS display 30 functional modules 38 step-by-step Python lessons I²C, UART, and GPIO expansion interfaces Portable carrying case included Specifications Main Processor Jetson Orin Nano Number of Sensors 30 Sensor Board Design Integrated sensor board, no soldering or complex wiring required Screen 11.6-inch IPS Screen Screen Resolution 1366 x 768 Camera IMX219 8MP Expansion Interfaces 2x I²C, 1x UART, 1x IO D13, 1xIO D12 Programming Environment Based on Python Number of Tutorials 38 creative tutorials Target Audience Students, teachers, hardware enthusiasts Application Scenarios Ideal for learning AI programming, Jetson Orin Nano basics Dimensions 300 x 200 x 100 mm Module List Module Quantity Temperature & Humidity Sensor 1 pcs Button 4 pcs Ultrasonic Ranging Sensor 1 pcs Light Sensor 1 pcs Linear Potentiometer 1 pcs Buzzer 1 pcs LCD 1 pcs Infrared Remote 1 pcs Relay 1 pcs NFC 1 pcs PIR Motion Sensor 1 pcs Joystick 1 pcs 4-Digital Display 1 pcs LED 1 pcs Microphone 1 pcs Speaker 1 pair Vibration Motor 1 pcs Touch Sensor 1 pcs 8x8 RGB Matrix 1 pcs Atmospheric pressure sensor 1 pcs Tilt Switch 1 pcs Stepper Motor 1 pcs Accelerometer & Gyro 1 pcs Gas Sensor (MQ2) 1 pcs Hall Sensor 1 pcs Rotary Encoder 1 pcs U-shaped photoelectric switch 1 pcs NTC 1 pcs Servo 2 pcs Monocular camera 1 pcs Included 1x Elecrow AI Starter Kit for Jetson Orin Nano 1x IR Remote Control 1x NFC Card 1x 128 GB SD Card 1x 40-pin GPIO Cable 2x 22-pin FPC Cable 2x 24-pin FPC Cable 1x Jetson DP & USB Adapter Board Not included NVIDIA Jetson Orin Nano Downloads Manual Wiki OpenClaw Install and Config Guide

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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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The Joy-Pi Advanced is a compact and powerful device that allows you to realize your projects quickly and easily. Whether you already have a lot of experience, or next to none, the Joy-Pi Advanced lets you unleash your creativity. Thanks to its compatibility with a wide range of platforms, including Raspberry Pi, Raspberry Pi Pico, Arduino Nano, BBC micro:bit, and NodeMCU ESP32, you can easily and quickly access your preferred platform. In addition, the Joy-Pi Advanced features more than 30 stations, lessons, and modules, giving you an unlimited variety of ways to get your projects done. With the self-developed learning center, you can not only improve your skills but also create new projects. The learning center offers a wealth of information and tutorials that will guide you step by step through your projects. Joy-Pi Advanced is characterized in particular by its intelligent switch units, which allow an extended use of the available pins. A total of three switch units are integrated, each equipped with 12 individual switches that provide precise control of the connected sensors and modules. This system solves the well-known problem of limited pin count that occurs with conventional microcontrollers. The switch units allow you to operate a large number of sensors and modules in parallel by switching them on and off individually. This simulates multiple pin assignment, allowing you to exploit the full power of your projects without compromising functionality. By combining innovative adapter boards and the micro:bit slot, you can achieve seamless compatibility with a wide range of microcontrollers such as Raspberry Pi Pico, NodeMCU ESP32, micro:mit and Arduino Nano. The specially developed adapter boards are designed to perfectly match the respective microcontroller. By plugging the microcontroller onto the appropriate adapter board and then plugging it into the micro:bit slot, the Joy-Pi Advanced quickly and easily becomes compatible with the different microcontrollers. This allows seamless integration of your preferred platform and the ability to combine the strengths of the different microcontrollers in your projects. This way, you can fully focus on your creative projects without worrying about the compatibility of different microcontrollers. The Joy-Pi Advanced simplifies the development process and gives you the possibility to design your projects flexibly and individually. Features Highly integrated development platform & learning center Fast, easy & wireless combination of various sensors & actuators Installation option for Raspberry Pi 4 Compatible with various microcontrollers Self-developed, didactic learning platform for Raspberry Pi & Windows Specifications Compatible to Raspberry Pi 4, Arduino Nano, NodeMCU ESP32, BBC micro:bit, Raspberry Pi Pico Installed sensors, actuators & components 39 Learning platform Over 40 entries in the know-ledge database, 10 projects, 10 learning tasks, 14 visions Displays 7-segment display, 16x2 display, 1.8“ TFT display, 0.96" OLED display, 8x8 RGB matrix Sensors DS18B20, shock sensor, hall sensor, barometer, sound sensor, gyroscope, PIR sensor, Light barrier, NTC, Light sensor, 6x touch sensor, color sensor, ultrasonic distance sensor, DHT11 temperature & humidity sensor Control Joystick, 5x switches, potentiometer, rotary encoder, 4x4 button matrix, relays, PWM fan Motors Servo interface, Stepper motor interface, Vibration motor Measuring & conversion modules Analog-Digital Converter, Level converter, voltmeter, Variable voltage supply Other components RTC real time clock, buzzer, EEPROM memory, infrared receiver, breadboard, RFID reader Adapter boards Adapter for NodeMCU ESP32, Arduino Nano & Raspberry Pi Pico, Board connectors for Raspberry Pi & External Boards Electronic components Infrared remote control, RFID chip, RFID card, 6x alligator clips, microSD card reader, servo motor, stepper motor, 32 GB microSD card Components 40x resistors, 3x green LEDs, 3x yellow LEDs, 3x red LEDs, 1x transistor, 5x buttons, 1x potentiometer, 2x capacitors Other accessories Screw assortment, screwdriver, accessory storage bag, power supply & power cable, servo mount Power supply Built-in power supply: 36 W, 12 V, 3 A Case connector: Small device plug C8 Voltage outputs 12 V, 5 V, 3.3 V, Variable voltage output (2-11 V) Data buses & signal outputs I²C, SPI, Analog to digital converter Battery (RTC) CR2032 Dimensions 327 x 200 x 52 mm Included Raspberry Pi 4 (8 GB RAM) Downloads Joy-Pi website Datasheet Manual

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This bundle includes the Arduino UNO Q (2 GB) and the book "Arduino UNO Q and AI". The Arduino UNO Q is the first UNO board with a hybrid dual-brain architecture, combining a powerful Linux processor with a real-time microcontroller – bringing advanced computing and precise control together on one board. Powered by a Qualcomm Dragonwing QRB2210 MPU running Debian Linux and a STM32U585 MCU for real-time tasks, the UNO Q is built for next-generation applications. From Edge Computing and AI to robotics and automation, it delivers high performance without sacrificing ease of use. Simply connect your peripherals and get started – no extra hardware required. Features Dual-core architecture: Linux MPU + real-time MCU Qualcomm Dragonwing QRB2210 with Debian Linux support STM32U585 microcontroller for deterministic control Runs Arduino sketches via Zephyr OS Ideal for AI, IoT, robotics, and industrial projects Specifications Microprocessor (MPU) Qualcomm Dragonwing QRB2210:Quad-core Arm Cortex-A53 @ 2.0 GHzAdreno GPU 3D graphics accelerator2× ISP (13 MP + 13 MP or 25 MP) @ 30 fps Microcontroller (MCU) STM32U585Arm Cortex-M33 up to 160 MHz2 MB flash memory786 KB SRAM RAM 2 GB LPDDR4 Power Supply From USB-C connector 5 V max at 3 AInput Voltage (VIN): 7-24 V Storage 16 GB eMMC USB 1× USB-C port with host/device role switching, power role switch and video output Connectivity Wi-Fi 5 (2.4/5 GHz) with onboard antennaBluetooth 5.1 with onboard antenna Interfaces I²C/I³CSPIPWMCANUARTPSSIGPIOJTAGADC Video Video output support via USB-CMIPI DSI pins on JMEDIA header Extra 4× RGB user-controllable LEDs8×13 Blue LED Matrix1× Qwiic connector voltage 3V3, I²C1× User push-buttonJCTL: MPU Remote Debug connector Audio Microphone IN / Headphone OUT / Line OUT on JMISC MPU Operating System Linux Debian OS with upstream support Real-time Operating System Arduino Core on Zephyr OS Containerization Docker and Docker Compose support Support Operating Systems for Arduino App Lab Windows: Windows 10 or later (64-bit)macOS: macOS 11 or later (64-bit)Linux: Ubuntu 22.04 or later, and Debian Trixie (64-bit) Dimensions 68.85 × 53.34 mm (UNO form factor) Downloads Datasheet User Manual Pinout Schematics Book: Arduino UNO Q and AI – 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. This bundle contains: Arduino UNO Q (2 GB) (normal price: €50) Book: Arduino UNO Q and AI (normal price: €35)

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. MultiRF Dev BoardA Platform for Evaluating Short- and Long-Range Wireless Protocols Elektor at 65Disrupting Electronics Since 1961 Wi-Fi-Based Person Detection on an ESP32When Your Router Becomes a Motion Sensor Wireless ScalesFour Small Scales = One Big Scale Walter, the Compact IoT ModuleESP32-S3 SoC, LTE-M/NB-IoT 5G Modem, and GNSS Receiver 3- and 4-Wire RTD Sensors ConditioningWith Full-Scale Adjustment and Cable Compensation 3-in-1 2-Channel Oscilloscope/Generator/MultimeterA Review of The Fnirsi 2D15P electronica Fast Forward 2026 Invites Startups and Industry Partners EcologgingA Modular Environmental IoT Station for Field Research Wireless Connectivity in Medical ApplicationsAlways on the Pulse with Bluetooth LE AudiotronicsHum Reduction Increasing Agricultural Efficiency with AI Modeling and SensorsBoosting Agricultural Productivity OPC UA — An OverviewPlatform-Independent Data Exchange Redox Meter Instrumentation Amplifier for Physics and Engineering Experiments Active Differential Audio FiltersFor Professional Crossovers and More Elektor Community Perspectives on IoT & Sensors Telegram-Controlled Water Heater Interface ModuleA Solution Based on an ESP32 and Arduino Software 2026: An AI OdysseyWhatever Happened to Fuzzy Logic? Err-lectronics Alarm Signal Injector Plus PowerTools for Finding Broken Wires

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Elektor GREEN en GOLD leden kunnen deze uitgave hier downloaden. Nog geen lid? Klik hier om een lidmaatschap af te sluiten. De ESP-BLASTEen mini ESP32 raketdrone die ruim 100 km/u vliegt STM32Cube Innovation-ChallengeDoe mee met je beste STM32C5-ontwerp Wireless workshop (1)Radiomodules uitgelegd: 433 MHz CC1101 sub-GHz-transceiver AM-zenderMet sinus- en blokgolfgenerator op Raspberry Pi Pico AudiotronicaDe vervormingsfactor CoffeeCallerOmroepsysteem met mesh-netwerk en Zephyr gebaseerde software Elektor wordt 65Projecten uit voorgaande september- en oktobermaanden Bluetooth Channel Sounding voor het volgen van objectenAfstandsmeting met centimeterprecisie voor het IoT van de volgende generatie 2026: Een AI-odysseeKwantumcomputing is geen volgende GPU Om de cloud te beveiligen, is edge-beveiliging nodig Eerste ervaringen met de HackRF ProPraktische tests met de nieuwe SDR-hardware Modemupgrade van GPRS/2G naar LTE/4GEen draadloos alarmsysteem als voorbeeld Lusvormige antenne met RF-bouwstenenDeel 1: Een zelfbouw kortegolfantenne met instelbare richtingsgevoeligheid Internetradio naar AM-converterMet een ESP32-S3 als zender Err-lectronics Mioty, een overzichtFraunhofer's aanpak van LPWAN WerkbankwijsheidPraktische tips van experts Walter, de compacte IoT-moduleDeel 2: Toegang tot weer- en datadiensten

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Program, build, and master 60+ projects with the Wireless RP2040 The Raspberry Pi Pico and Pico W are based on the fast, efficient, and low-cost dual-core ARM Cortex M0+ RP2040 microcontroller chip running at up to 133 MHz and sporting 264 KB of SRAM and 2 MB of Flash memory. Besides spacious memory, the Pico and Pico W offer many GPIO pins, and popular peripheral interface modules like ADC, SPI, I²C, UART, PWM, timing modules, a hardware debug interface, and an internal temperature sensor. The Raspberry Pi Pico W additionally includes an on-board Infineon CYW43439 Bluetooth and Wi-Fi chipset. At the time of writing this book, the Bluetooth firmware was not yet available. Wi-Fi is however fully supported at 2.4 GHz using the 802.11b/g/n protocols. This book is an introduction to using the Raspberry Pi Pico W in conjunction with the MicroPython programming language. The Thonny development environment (IDE) is used in all of the 60+ working and tested projects covering the following topics: Installing the MicroPython on Raspberry Pi Pico using a Raspberry Pi or a PC Timer interrupts and external interrupts Analogue-to-digital converter (ADC) projects Using the internal temperature sensor and external sensor chips Using the internal temperature sensor and external temperature sensor chips Datalogging projects PWM, UART, I²C, and SPI projects Using Bluetooth, WiFi, and apps to communicate with smartphones Digital-to-analogue converter (DAC) projects All projects are tried & tested. They can be implemented on both the Raspberry Pi Pico and Raspberry Pi Pico W, although the Wi-Fi-based subjects will run on the Pico W only. Basic programming and electronics experience are required to follow the projects. Brief descriptions, block diagrams, detailed circuit diagrams, and full MicroPython program listings are given for all projects.

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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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