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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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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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For a limited time, the Joy-Pi Advanced is available in a great-value bundle with a Raspberry Pi 4 (8 GB)! 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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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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The Elektor Arduino Nano MCCAB Training Board contains all the components (incl. Arduino Nano) required for the exercises in the "Microcontrollers Hands-on Course for Arduino Starters", such as light-emitting diodes, switches, pushbuttons, acoustic signal transmitters, etc. External sensors, motors or assemblies can also be queried or controlled with this microcontroller training system. Specifications (Arduino Nano MCCAB Training Board) Power Supply Via the USB connection of the connected PC or an external power supply unit (not included) Operating Voltage +5 Vcc Input Voltage All inputs 0 V to +5 V VX1 and VX2 +8 V to +12 V (only when using an external power supply) Hardware periphery LCD 2x16 characters Potentiometer P1 & P2 JP3: selection of operating voltage of P1 & P2 Distributor SV4: Distributor for the operating voltagesSV5, SV6: Distributor for the inputs/outputs of the microcontroller Switches and buttons RESET button on the Arduino Nano module 6x pushbutton switches K1 ... K6 6x slide switches S1 ... S6 JP2: Connection of the switches with the inputs of the microcontroller Buzzer Piezo buzzer Buzzer1 with jumper on JP6 Indicator lights 11 x LED: Status indicator for the inputs/outputs LED L on the Arduino Nano module, connected to GPIO D13 JP6: Connection of LEDs LD10 ... LD20 with GPIOs D2 ... D12 Serial interfacesSPI & I²C JP4: Selection of the signal at pin X of the SPI connector SV12 SV9 to SV12: SPI interface (3.3 V/5 V) or I²C interface Switching output for external devices SV1, SV7: Switching output (maximum +24 V/160 mA, externally supplied) SV2: 2x13 pins for connection of external modules 3x3 LED matrix(9 red LEDs) SV3: Columns of the 3x3 LED matrix (outputs D6 ... D8) JP1: Connection of the rows with the GPIOs D3 ... D5 Software Library MCCABLib Control of hardware components (switches, buttons, LEDs, 3x3 LED matrix, buzzer) on the MCCAB Training Board Operating Temperature Up to +40 °C Dimensions 100 x 100 x 20 mm Specifications (Arduino Nano) Microcontroller ATmega328P Architecture AVR Operating Voltage 5 V Flash Memory 32 KB, of which 2 KB used by bootloader SRAM 2 KB Clock Speed 16 MHz Analog IN Pins 8 EEPROM 1 KB DC Current per I/O Pins 40 mA on one I/O pin, total maximum 200 mA on all pins together Input Voltage 7-12 V Digital I/O Pins 22 (6 of which are PWM) PWM Output 6 Power Consumption 19 mA Dimensions 18 x 45 mm Weight 7 g Included 1x Elektor Arduino Nano Training Board MCCAB 1x Arduino Nano

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The Internet of Things (IoT) is a new concept in intelligent automation and intelligent monitoring using the Internet as the communications medium. The “Things” in IoT usually refer to devices that have unique identifiers and are connected to the Internet to exchange information with each other. Such devices usually have sensors and/or actuators that can be used to collect data about their environments and to monitor and control their environments. The collected data can be processed locally or it can be sent to centralized servers or to the cloud for remote storage and processing. For example, a small device at the size of a matchbox can be used to collect data about the temperature, relative humidity and the atmospheric pressure. This data can be sent and stored in the cloud. Anyone with a mobile device can then access and monitor this data at any time and from anywhere on Earth provided there is Internet connectivity. In addition, users can for example, adjust the central heating remotely using their mobile devices and accessing the cloud. This book is written for students, for practising engineers and for hobbyists who want to learn more about the building blocks of an IoT system and also learn how to setup an IoT system using these blocks. Chapter 1 is an introduction to the IoT systems. In Chapter 2, the basic concepts and possible IoT architectures are discussed. The important parts of any IoT system are the sensors and actuators and they are described briefly in Chapter 3. The devices in an IoT system usually communicate with each other and the important aspect of IoT communication is covered in Chapter 4. Chapter 5 proceeds with the features of some of the commonly used development kits. One of these, the Clicker 2 for PIC18FJ manufactured by mikroElektronika, can be used as a processor in IoT systems and its features are described in detail in Chapter 6. A popular microcontroller C language, mikroC Pro for PIC gets introduced in Chapter 7. Chapter 8 covers the use of a click board with the Clicker 2 for PIC18FJ development kit. Similarly, the use of a sensor click board is described as a project in Chapter 9, and an actuator board in Chapter 10. Chapters 11 and 12 cover Bluetooth and Wi-Fi technologies in microcontroller based systems, and the remaining chapters of the book demo the creation of a simple Wi-Fi based IoT system with cloud-based data storage. This book has been written with the assumption that the reader has taken a course on digital logic design and has been exposed to writing programs using at least one high-level programming language. Knowledge of the C programming language will be very useful. Also, familiarity with at least one member of the PIC series of microcontrollers (e.g. PIC16 or PIC18) will be an advantage. The knowledge of assembly language programming is not required because all the projects in the book are based on using the C language. If you are a total beginner in programming you can still access the e-book, but first you are advised to study introductory books on microcontrollers.

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