Search results for "beagley or ai or sbc or with or gpu or dsp or and or ai or accelerators"

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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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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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 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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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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The Elektor Audio DSP FX Processor combines an ESP32 microcontroller and an ADAU1701 Audio DSP from Analog Devices. Besides a user-programmable DSP core, the ADAU1701 has high-quality analog-to-digital and digital-to-analog converters built-in and features an I²S port. This makes it suitable as a high-quality audio interface for the ESP32. Programs for the ESP32 can be created with Arduino, Platform IO, CMake or by using the Espressif IDF in another way. Programs for the ADAU7101 audio DSPs are created with the free visual programming tool SigmaStudio by dragging and dropping pre-defined algorithm blocks on a canvas. Applications Bluetooth/Wi-Fi audio sink (e.g. loudspeaker) & source Guitar effect pedal (stomp box) Music synthesizer Sound/function generator Programmable cross-over filter for loudspeakers Advanced audio effects processor (reverb, chorus, pitch shifting, etc.) Internet-connected audio device DSP experimentation platform Wireless MIDI MIDI to CV converter and many more... Specifications ADAU1701 28-/56-bit, 50-MIPS digital audio processor supporting sampling rates of up to 192 kHz ESP32 32-bit dual-core microcontroller with Wi-Fi 802.11b/g/n and Bluetooth 4.2 BR/EDR and BLE 2x 24-bit audio inputs (2 V RMS, 20 kΩ) 4x 24-bit audio outputs (0.9 V RMS, 600 Ω) 4x Control potentiometer MIDI in- and output I²C expansion port Multi-mode operation Power supply: 5 V DC USB or 7.5-12 V DC (barrel jack, center pin is GND) Current consumption (average): 200 mA Included 1x ESP32 Audio DSP FX Processor board (assembled) 1x ESP32-PICO-KIT 2x Jumpers 2x 18-pin headers (female) 4x 10 KB potentiometers Downloads Documentation GitHub

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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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Over 40 Fully Tested ESP32 Projects Using Arduino IDE and the LVGL Graphics Library This bundle includes the ESP32 Cheap Yellow Display (CYD) – a compact development board combining a standard ESP32 microcontroller with a 320x240 pixel TFT color display. The board also features multiple connectors for GPIO, serial communication (TX/RX), power, and ground. The built-in display is a major advantage, allowing users to create complex, graphics-based projects without the need for external LCDs or displays. The accompanying book introduces the CYD board's hardware and on-board connectors in detail. It provides a range of beginner to intermediate-level projects developed using the popular Arduino IDE 2.0. Both basic graphics functions and the powerful LVGL graphics library are covered, with practical projects illustrating each approach. All included projects have been fully tested and are ready to use. The book provides block diagrams, circuit schematics, complete code listings, and step-by-step explanations. With the LVGL library, readers can create modern, full-color graphical interfaces using widgets such as buttons, labels, sliders, calendars, keyboards, charts, tables, menus, animations, and more. ESP32 Cheap Yellow Display Board This development board (also known as "Cheap Yellow Display") is powered by the ESP-WROOM-32, a dual-core MCU with integrated Wi-Fi and Bluetooth capabilities. It operates at a main frequency of up to 240 MHz, with 520 KB SRAM, 448 KBROM, and a 4 MB Flash memory. The board features a 2.8-inch display with a resolution of 240x320 and resistive touch. Furthermore, the board includes a backlight control circuit, touch control circuit, speaker drive circuit, photosensitive circuit, and RGB-LED control circuit. It also provides a TF card slot, serial interface, DHT11 temperature and humidity sensor interface, and additional IO ports. The module supports development in Arduino IDE, ESP-IDE, MicroPython, and Mixly. Applications Image transmission for Smart Home device Wireless monitoring Smart agriculture QR wireless recognition Wireless positioning system signal And other IoT applications Specifications Microcontroller ESP-WROOM-32 (Dual-core MCU with integrated Wi-Fi and Bluetooth) Frequency Up to 240 MHz (computing power is up to 600 DMIPS) SRAM 520 KB ROM 448 KB Flash 4 MB Operating voltage 5 V Power consumption approx. 115 mA Display 2.8-inch color TFT screen (240 x 320) Touch Resistive Touch Driver chip ILI9341 Dimensions 50 x 86 mm Weight 50 g Downloads GitHub This bundle contains: The ESP32 Cheap Yellow Display Book (normal price: €35) ESP32 Cheap Yellow Display Board (normal price: €25) 1x ESP32 Dev Board with 2.8" Display and acrylic Shell 1x Touch pen 1x Connector cable 1x USB cable

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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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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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Build Your Own Vintage Radio Broadcaster The Elektor AM Transmitter Kit allows streaming audio to vintage AM radio receivers. Based on a Raspberry Pi Pico microcontroller module, the AM Transmitter can transmit on 32 frequencies in the AM band, from 500 kHz up to 1.6 MHz in 32 steps of approx. 35 kHz. The frequency is selected with a potentiometer and shown on a 0.96" OLED display. A pushbutton allows toggles the transmitting mode between On and Off. The range of the transmitter depends on the antenna. The onboard antenna provides a range of a few centimeters, requiring the AM Transmitter to be placed close to or inside the radio. An external loop antenna (not included) can be connected to increase the range. The Elektor AM Transmitter Kit comes as a kit of parts that you must solder to the board yourself. Features The board is compatible with a Hammond 1593N enclosure (not included).A 5 VDC power supply with micro-USB connector (e.g., an old phone charger) is needed to power the kit (not included). Current consumption is 100 mA. The Arduino software (requiring Earle Philhower’s RP2040 Boards Package) for the Elektor AM Transmitter Kit plus more information is available at the Elektor Labs page of this project. Component List Resistors R1, R4 = 100 Ω R2, R3, R8 = 10 kΩ R5, R6, R9, R10, R11 = 1 kΩ R7 = optional (not included) P1 = potentiometer 100 kΩ, linear Capacitors C1 = 22 µF 16V C2, C4 = 10 nF C3 = 150 pF Miscellaneous K1 = 4×1 pin socket K2, K3 = 3.5 mm socket Raspberry Pi Pico pushbutton, angle mount 0.96" monochrome I²C OLED display PCB 150292-1

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This complete STM32 microcontroller programming course features a textbook, a component kit, hands-on projects, and a comprehensive online course. 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 STM32 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 MicroPython 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 on the STM32 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 STM32 NUCLEO-F411RE microcontroller board Book: MicroPython for STM32 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

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