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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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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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Over 180 Projects with Raspberry Pi, Pico W, Arduino, and ESP32 This bundle contains the Universal Maker Sensor Kit, which consists of many sensors, actuators, displays, and motors. It’s perfect for environmental monitoring, smart home projects, robotics, and game controllers. The new Elektor book describes the design of many projects using the kit together with the popular Raspberry Pi, Raspberry Pi Pico W, Arduino Uno, and the ESP32 family of development boards. You can choose any of these development boards for your projects and either use the provided programs as they are, or modify these programs to suit your applications. This bundle contains: Book: Universal Maker Sensor Kit (normal price: €45) Universal Maker Sensor Kit for Raspberry Pi, Pico W, Arduino, ESP32 (normal price: €70) Book: Universal Maker Sensor Kit Learn to use more than 35 Sensors and Actuators with C++, Python, and MicroPython This book contains over 180 projects for all four major development boards (Arduino, Raspberry Pi, Pico W, and ESP32). Depending on the development board, projects are available in the C, Python, or MicroPython programming languages. The project titles, brief descriptions, wiring diagrams, and full program listings together with their detailed descriptions are given in the guide. Universal Maker Sensor Kit (for Raspberry Pi, Pico W, Arduino, ESP32) Discover endless creativity with the Universal Maker Sensor Kit, designed for use with Raspberry Pi, Pico W, Arduino, and ESP32. This versatile kit offers compatibility across popular development platforms, including Arduino Uno R4 Minima/WiFi, Uno R3, Mega 2560, Raspberry Pi 5, 4, 3B+, 3B, Zero, Pico W, and ESP32. Featuring over 35 sensors, actuators, and displays, it's perfect for projects ranging from environmental monitoring and smart home automation to robotics and interactive gaming. Step-by-step tutorials in C/C++, Python, and MicroPython guide beginners and experienced makers alike through 169 exciting projects. Features Wide Compatibility: Fully supports Arduino (Uno R3, Uno R4 Minima/WiFi, Mega 2560), Raspberry Pi (5, 4, 3B+, 3B, Zero, Pico W), and ESP32, enabling extensive flexibility across numerous development platforms. Includes instructions for building 169 projects. Comprehensive Components: Features more than 35 sensors, actuators, and display modules suitable for diverse projects such as environmental monitoring, smart home automation, robotics, and interactive game controllers. Detailed Tutorials: Provides clear, step-by-step tutorials covering Arduino, Raspberry Pi, Pico W, ESP32, and each included component. Tutorials are available in C/C++, Python, and MicroPython, catering effectively to both beginners and experienced makers. Suitable for All Skill Levels: Offers structured projects designed to guide users seamlessly from beginner to advanced proficiency in electronics and programming, enhancing creativity and technical expertise. Kit includes Breadboard Button Module Capacitive Soil Moisture Module Flame Sensor Module Gas/Smoke Sensor Module (MQ2) Gyroscope & Accelerometer Module (MPU6050) Hall Sensor Module Infrared Speed Sensor Module IR Obstacle Avoidance Sensor Module Joystick Module PCF8591 ADC DAC Converter Module Photoresistor Module PIR Motion Module (HC-SR501) Potentiometer Module Pulse Oximeter and Heart Rate Sensor Module (MAX30102) Raindrop Detection Module Real Time Clock Module (DS1302) Rotary Encoder Module Temperature Sensor Module (DS18B20) Temperature and Humidity Sensor Module (DHT11) Temperature, Humidity & Pressure Sensor (BMP280) Time of Flight Micro-LIDAR Distance Sensor (VL53L0X) Touch Sensor Module Ultrasonic Sensor Module (HC-SR04) Vibration Sensor Module (SW-420) Water Level Sensor Module I²C LCD 1602 OLED Display Module (SSD1306) RGB LED Module Traffic Light Module 5 V Relay Module Centrifugal Pump L9110 Motor Driver Module Passive Buzzer Module Servo Motor (SG90) TT Motor ESP8266 Module JDY-31 Bluetooth Module Power Supply Module Documentation Online Tutorial

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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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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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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 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 with Arduino 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 with the ESP32 using the Arduino 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 C/C++ Using Arduino 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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Book: Mastering the Arduino Uno R4 Based on the low-cost 8-bit ATmega328P processor, the Arduino Uno R3 board is likely to score as the most popular Arduino family member, and this workhorse has been with us for many years. Eleven years later, the long-overdue successor, the Arduino Uno R4, was released. It is built around a 48 MHz, 32-bit Arm Cortex-M4 microcontroller and provides significantly expanded SRAM and Flash memory. Additionally, a higher-precision ADC and a new DAC are added to the design. The Uno R4 board also supports the CAN Bus with an interface. Two versions of the board are available: Uno R4 Minima, and Uno R4 WiFi. This book is about using these new boards to develop many different and interesting projects with just a handful of parts and external modules. All projects described in the book have been fully tested on the Uno R4 Minima or the Uno R4 WiFi board, as appropriate. The project topics include the reading, control, and driving of many components and modules in the kit as well as on the relevant Uno R4 board, including LEDs 7-segment displays (using timer interrupts) LCDs Sensors RFID Reader 4x4 Keypad Real-time clock (RTC) Joystick 8×8 LED matrix Motors DAC (Digital-to-analog converter) LED matrix WiFi connectivity Serial UART CAN bus Infrared controller and receiver Simulators … all in creative and educational ways with the project operation and associated software explained in great detail. Arduino Uno R4 WiFi The Arduino Uno R4 is powered by the Renesas RA4M1 32-bit ARM Cortex-M4 processor, providing a significant boost in processing power, memory, and functionality. The WiFi version comes with an ESP32-S3 WiFi module in addition to the RA4M1, expanding creative opportunities for makers and engineers. The Arduino Uno R4 runs at 48 MHz, which provides a 3x increase over the popular Uno R3. Additionally, SRAM has been upgraded from 2 kB to 32 kB, and flash memory from 32 kB to 256 kB to support more complex projects. Responding to community feedback, the USB port is now USB-C, and the maximum power supply voltage has been raised to 24 V with an enhanced thermal design. The board includes a CAN bus and an SPI port, enabling users to reduce wiring and perform parallel tasks by connecting multiple shields. A 12-bit analog DAC is also provided on the board. Specifications Microcontroller Renesas RA4M1 (ARM Cortex-M4) USB USB-C Programming Port Pins Digital I/O Pins 14 Pins Analog input pins 6 DAC 1 RTC 1 PWM pins 6 Communication UART 1x I²C 1x SPI 1x Qwiic I²C connector 1x CAN 1x CAN Bus Power Circuit operating voltage 5 V Input voltage (VIN) 6-24 V DC Current per I/O Pin 8 mA Clock speed Main core 48 MHz Memory RA4M1 256 kB Flash, 32 kB RAM LED Matrix 12 x 8 (96 red LEDs) Dimensions 68.9 x 53.4 mm Downloads Datasheet Schematics This bundle contains: Book: Mastering the Arduino Uno R4 (normal price: €45) Arduino Uno R4 WiFi (normal price: €30)

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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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Discover endless creativity with the Universal Maker Sensor Kit, designed for use with Raspberry Pi, Pico W, Arduino, and ESP32. This versatile kit offers compatibility across popular development platforms, including Arduino Uno R4 Minima/WiFi, Uno R3, Mega 2560, Raspberry Pi 5, 4, 3B+, 3B, Zero, Pico W, and ESP32. Featuring over 35 sensors, actuators, and displays, it's perfect for projects ranging from environmental monitoring and smart home automation to robotics and interactive gaming. Step-by-step tutorials in C/C++, Python, and MicroPython guide beginners and experienced makers alike through 169 exciting projects. Features Wide Compatibility: Fully supports Arduino (Uno R3, Uno R4 Minima/WiFi, Mega 2560), Raspberry Pi (5, 4, 3B+, 3B, Zero, Pico W), and ESP32, enabling extensive flexibility across numerous development platforms. Includes instructions for building 169 projects. Comprehensive Components: Features more than 35 sensors, actuators, and display modules suitable for diverse projects such as environmental monitoring, smart home automation, robotics, and interactive game controllers. Detailed Tutorials: Provides clear, step-by-step tutorials covering Arduino, Raspberry Pi, Pico W, ESP32, and each included component. Tutorials are available in C/C++, Python, and MicroPython, catering effectively to both beginners and experienced makers. Suitable for All Skill Levels: Offers structured projects designed to guide users seamlessly from beginner to advanced proficiency in electronics and programming, enhancing creativity and technical expertise. Included Breadboard Button Module Capacitive Soil Moisture Module Flame Sensor Module Gas/Smoke Sensor Module (MQ2) Gyroscope & Accelerometer Module (MPU6050) Hall Sensor Module Infrared Speed Sensor Module IR Obstacle Avoidance Sensor Module Joystick Module PCF8591 ADC DAC Converter Module Photoresistor Module PIR Motion Module (HC-SR501) Potentiometer Module Pulse Oximeter and Heart Rate Sensor Module (MAX30102) Raindrop Detection Module Real Time Clock Module (DS1302) Rotary Encoder Module Temperature Sensor Module (DS18B20) Temperature and Humidity Sensor Module (DHT11) Temperature, Humidity & Pressure Sensor (BMP280) Time of Flight Micro-LIDAR Distance Sensor (VL53L0X) Touch Sensor Module Ultrasonic Sensor Module (HC-SR04) Vibration Sensor Module (SW-420) Water Level Sensor Module I²C LCD 1602 OLED Display Module (SSD1306) RGB LED Module Traffic Light Module 5 V Relay Module Centrifugal Pump L9110 Motor Driver Module Passive Buzzer Module Servo Motor (SG90) TT Motor ESP8266 Module JDY-31 Bluetooth Module Power Supply Module Documentation Online Tutorial

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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! Die Open-Source-Prozessorarchitektur RISC-V16 Boards und MCUs, die Sie kennen sollten Audio-Player mit FPGA und EqualizerTeil 1. Digitale Audiosignale mischen mit einem MKR Vidor 4000 von Arduino Laserkopf für Pico-basierte SanduhrZeichnen mit Licht Nehmen Sie teil am STM32 Edge AI Contest! Umweltüberwachung von Pflanzen mit mehreren SensorenDrahtlose Messung der Wasserversorgung und Lichtverhältnisse Maixduino: Automatischer KI-TüröffnerGesichtserkennung mit einer Kamera Embedded-Elektronik 2024KI wird die Branche neu definieren Ladungsbasiertes In-Memory Compute bei EnCharge AI KI-Inferencing bei 10-fach geringerer Leistungsaufnahme zu 20-fach geringeren Kosten Click-Board hilft bei der Entwicklung und dem Training von ML-Modellen für die Schwingungsanalyse Der Elektor Mini-WheelieEin Bausatz für einen selbstbalancierenden Roboter MCU, ich sehe dich!MCUViewer, ein Open-Source-Multiplattform-Debugging-Werkzeug USB-2.0-IsolatorGeräte galvanisch isoliert per USB verbinden Eingriff vor dem SchadenPredictive Maintenance in der Praxis SPoE - Elektromagnetische VerträglichkeitSingle-Pair mit Power-over-Ethernet im EMV-Fokus Retro-TechnikWie das Farbfernsehen eine neue Welt schuf EKG-MonitorMit Hexabitz-Modulen und einem STM32CubeMonitor Der Kampf um KI at the Edge HaLow erreicht Rekorddistanz von 16 km für WLAN bei 900 MHz Erster CHERI RISC-V-Embedded Chip und Early Access Programm Die dritte Generation der Waldbrandfrüherkennung nutzt Satellitenverbindungen Aus dem Leben gegriffenDie Qual der Wahl Aller Anfang......ist nicht schwer: Wir setzen die Filterung und Klangregelung fort. Riesen-LED-UhrNeuauflage eines Elektor-Klassikers Ein modularer Ansatz für die SensorprüfungDas Sensor Evaluation Board mit ESP32-S3 2025: Eine Odyssee in die KIDer Aufstieg der Basismodelle und ihre Rolle bei der Demokratisierung der KImocratizing AI Standalone MIDI-Synthesizer mit Raspberry PTeil 1: Eine Plattform für Edge-KI-Experimente vorbereiten Projekt 2.0Korrekturen, Updates und Leserbriefe CPU, GPU, DSP, FPGA; ein universeller KI-RISC-V-Prozessor kann alles! CEO-Interview: Ventivas dünne und kühle Technologie Dual-Core-Programmierung beim Raspberry Pi PicoEinstieg in die Welt der parallelen Programmierung

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