Search results for "lora or nexus or board or arduino or mini or shape"

High-Performance LoRa Communication Device The Elecrow ThinkNode M5 is a compact, portable LoRa communication device designed for off-grid messaging, location sharing, and outdoor use. Powered by an ESP32-S3 processor and an SX1262 LoRa chip, it comes pre-installed with Meshtastic firmware and can be configured conveniently via Bluetooth using the official Meshtastic app. The integrated multi-GNSS module supports GPS, GLONASS, BeiDou, and QZSS for reliable positioning and location sharing. Messages and device information are displayed on the energy-efficient 1.54-inch e-paper screen, while the built-in 1,200 mAh rechargeable battery enables extended mobile operation. With its integrated LoRa antenna, compact housing, RTC, and support for both Meshtastic and MeshCore firmware, the ThinkNode M5 is a practical communication solution for hiking, camping, remote locations, and emergency situations where conventional mobile networks are unavailable. Features LoRa communication Multi-GNSS positioning 1,200 mAh rechargeable battery 1.54-inch e-paper display Built-in RTC Compatible with MeshCore Compatible with Meshtastic Specifications Main Processor (ESP32-S3) CPU/SoC Xtensa 32-bit LX7 dual-core processor, clocked at up to 240 MHz System Memory 512 KB SRAM, 8 MB PSRAM Storage 4 MB Flash, 384 KB ROM Firmware Meshtastic firmware is fully compatible, and the signal is transmitted in LoRa mode EPD (Electronic Paper Display) Display Size 1.54 inch EPD (monochrome Ink screen) Display Materials E-lnk (Electronic Ink） Resolution 200 x 200 Driver Chip SSD1681 (via SPI or I²C interface) Global Fresh Time 2s Wireless Communication Bluetooth Bluetooth Low Energy and Bluetooth 5.0 (phone configuration) LoRa SX1262 LoRa Module, EU 868 MHz（external antenna） Hardware Interfaces USB-C, RP-SMA Function GPS Location (GPS, GLONASS, BeiDou, QZSS), EPD Display, RTC, USB 2.0, PMU power management (built-in 1200 mAh lithium battery), buzzer, etc. Button Knob Switch, Function Button, Page Turn Button, GPS Switch, Reset Button LED Indicator Power supply, GPS/LoRa indication Others Power Input 5 V/1 A, supports USB or lithium battery power supply Power consumption The maximum working current is about 340 mA (CPU + LoRa module), and the low power consumption is about 34 uA Operating Temperature -10~50°C Storage Temperature -20~60°C Relative humidity 10-95%, @ 40°C (non-condensing) Enclosure ABS Plastic Dimensions 82 x 51.6 x 26.3 mm Weight 81 g Included 1x Elecrow ThinkNode M5 1x LoRa antenna 1x USB-C cable 1x Manual Downloads Manual

Read (+) (–)

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)

Read (+) (–)

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)

Read (+) (–)

Mit dem Elektor Arduino Nano Trainingsboard (MCCAB) eigene Projekte realisieren Der Mikrocontroller ist das wohl faszinierendste Teilgebiet der Elektronik, denn aufgrund der Vielzahl von Funktionen, die er auf seinem Chip vereinigt, ist er für den Entwickler ein universelles Multi-Tool zur Realisierung seiner Projekte. Praktisch jedes Gerät des täglichen Gebrauchs wird heute von einem Mikrocontroller gesteuert. Für einen elektronischen Laien blieb es aufgrund der Komplexität bisher allerdings ein Wunschtraum, eigene Ideen mit einem Mikrocontroller zu realisieren. Das Arduino-Konzept hat den Einsatz von Mikrocontrollern weitgehend vereinfacht, sodass jetzt auch Laien eigene Elektronik-Ideen mit einem Mikrocontroller verwirklichen können. Buch & Hardware im Bundle: 'Learning by Doing' Dieses im Bundle mitgelieferte Buch (im großen A4-Format) zeigt, wie man auch ohne große Erfahrung in Elektronik und Programmiersprachen eigene Projekte mit einem Mikrocontroller realisieren kann. Es ist ein Mikrocontroller-Praxiskurs für Einsteiger, denn nach einem Überblick über die Interna des Mikrocontrollers und einer Einführung in die Programmiersprache C liegt der Schwerpunkt des Kurses auf den praktischen Übungen. Der Leser eignet sich die erforderlichen Kenntnisse durch 'Learning by Doing' an: in dem umfangreichen Praxisteil mit 12 Projekten und 46 Übungen wird das im vorderen Teil des Buches Gelernte mit vielen Beispielen unterlegt. Die Übungen sind dabei so aufgebaut, dass der Bearbeiter eine Aufgabenstellung erhält, die er mit seinem im Theorieteil des Buches aufgebauten Wissen löst. Für jede Übung gibt es anschließend eine ausführlich erklärte und kommentierte Musterlösung, die dem Bearbeiter bei Problemen weiterhilft und die er mit seiner eigenen Lösung vergleichen kann. Arduino IDE In der Arduino IDE, einer Software-Entwicklungsumgebung, die kostenlos auf den eigenen PC heruntergeladen werden kann und die das gesamte Softwarepaket enthält, das für ein eigenes Mikrocontroller-Projekt benötigt wird, schreibt der Bearbeiter mit dem Editor der IDE seine Programme („Apps“) in der Programmiersprache C. Der in die Arduino IDE integrierte Compiler übersetzt sie in die Bits und Bytes, die der Mikrocontroller versteht und die dann über ein USB-Kabel in den Speicher des Mikrocontrollers auf dem Elektor Arduino Nano Trainingsboard (MCCAB) geladen werden. Externe Sensoren, Motoren oder Baugruppen abfragen oder steuern Das Elektor Arduino Nano Trainingsboard (MCCAB) enthält neben einem Mikrocontrollermodul Arduino Nano alle für die Übungen benötigten Bauteile wie Leuchtdioden, Schalter, Taster, akustische Signalgeber usw. Auch externe Sensoren, Motoren oder Baugruppen können mit diesem Mikrocontroller-Übungssystem abgefragt oder gesteuert werden. Technische Daten (Arduino Nano Trainingsboard MCCAB) Stromversorgung Über die USB-Verbindung des zur Erstellung der Programme sowieso angeschlossenen PCs oder ein externes Netzteil (nicht im Lieferumfang enthalten) Betriebsspannung +5 Vcc Eingangsspannung Alle Eingänge 0 V bis +5 V VX1 und VX2 +8 V bis +12 V (nur bei Verwendung eines externen Netzteils) Mikrocontrollermodul Arduino Nano Hardwareperipherie LCD 2x16 Zeichen Potenziometer P1 & P2 JP3: Auswahl der Betriebsspannung von P1 & P2 Verteiler SV4: Verteiler für die BetriebsspannungenSV5, SV6: Verteiler für die Ein-/Ausgänge des Mikrocontrollers Schalter und Taster RESET-Taster auf dem Arduino Nano-Modul6x Tastschalter K1 … K66x Schiebeschalter S1 … S6JP2: Verbindung der Schalter mit den Eingängen des Mikrocontrollers Summer Piezo-Summer Buzzer1 mit Steckbrücke auf JP6 Leuchtanzeigen LED L auf dem Arduino Nano-Modul, verbunden mit GPIO D1311x LED: Zustandsanzeige für die Ein-/AusgängeJP6: Verbindung der LEDs LD10 … LD20 mit den GPIOs D2 … D12 Serielle SchnittstellenSPI & I²C JP4: Auswahl des Signals an Pin X der SPI-Steckerleiste SV12SV9 bis SV12: SPI-Interface (3,3 V/5 V) bzw. I²C-Interface Schaltausgang für externe Geräte SV1, SV7: Schaltausgang (maximal +24 V/160 mA, extern zugeführt)SV2: 2x13 Pins zum Anschluss externer Module 3x3 LED-Matrix (9 rote LEDs) SV3: Spalten der 3x3 LED-Matrix (Ausgänge D6 … D8)JP1: Verbindung der Reihen mit den GPIOs D3 … D5 Software Library MCCABLib Steuerung der Hardware-Komponenten (Schalter, Taster, Leuchtdioden, 3x3 LED-Matrix, Summer) auf dem MCCAB Trainingsboard Betriebstemperatur bis +40 °C Abmessungen 100 x 100 x 20 mm Technische Daten (Arduino Nano) Mikrocontroller ATmega328P Architektur AVR Betriebsspannung 5 V Flashspeicher 32 KB, davon 2 KB vom Bootloader belegt SRAM 2 KB Taktfrequenz 16 MHz Analoge IN-Pins 8 EEPROM 1 KB DC-Strom pro I/O-Pin 40 mA an einem I/O-Pin, insgesamt maximal 200 mA an allen Pins gemeinsam Eingangsspannung 7-12 V Digitale I/O-Pins 22 (6 davon sind PWM-fähig) PWM-Ausgänge 6 Stromverbrauch 19 mA Abmessungen 18 x 45 mm Gewicht 7 g Lieferumfang Elektor Arduino Nano MCCAB Trainingsboard Arduino Nano Buch: Mikrocontroller-Praxiskurs für Arduino-Einsteiger

Read (+) (–)

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

Read (+) (–)

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

Read (+) (–)

The Arduino Pro Mini is a microcontroller board based on the ATmega328P. It has 14 digital input/output pins (of which 6 can be used as PWM outputs), 6 analog inputs, an on-board resonator, a reset button, and holes for mounting pin headers. A six pin header can be connected to an FTDI cable or SparkFun breakout board to provide USB power and communication to the board. The Arduino Pro Mini is intended for semi-permanent installation in objects or exhibitions. The board comes without pre-mounted headers, allowing the use of various types of connectors or direct soldering of wires. The pin layout is compatible with the Arduino Mini. The Arduino Pro Mini was designed and is manufactured by SparkFun Electronics. Specifications Microcontroller ATmega328P Board Power Supply 5-12 V Circuit Operating Voltage 5 V Digital I/O Pins 14 PWM Pins 6 UART 1 SPI 1 I²C 1 Analog Input Pins 6 External Interrupts 2 DC Current per I/O Pin 40 mA Flash Memory 32 KB of which 2 KB used by bootloader SRAM 2 KB EEPROM 1 KB Clock Speed 16 MHz Dimensions 18 x 33.3 mm (0.7 x 1.3") Downloads Eagle files Schematics

Read (+) (–)

Realize your own projects with the Elektor Arduino Nano MCCAB Training Board The microcontroller is probably the most fascinating subfield of electronics. Due to the multitude of functions, it combines on its chip, it is a universal multi-tool for developers to realize their projects. Practically every device of daily use today is controlled by a microcontroller. However, for an electronic layman, realizing his own ideas with a microcontroller has so far remained a pipe dream due to its complexity. The Arduino concept has largely simplified the use of microcontrollers, so that now even laymen can realize their own electronics ideas with a microcontroller. Book & Hardware in the Bundle: 'Learning by Doing' This book, which is included in the bundle, shows how you can realize your own projects with a microcontroller even without much experience in electronics and programming languages. It is a microcontrollers hands-on course for starters, because after an overview of the internals of the microcontroller and an introduction to the programming language C, the focus of the course is on the practical exercises. The reader acquires the necessary knowledge by 'learning by doing': in the extensive practical section with 12 projects and 46 exercises, what is learned in the front part of the book is underpinned with many examples. The exercises are structured in such a way that the user is given a task to solve using the knowledge built up in the theoretical part of the book. Each exercise is followed by a sample solution that is explained and commented on in detail, which helps the user to solve problems and compare it with his own solution. Arduino IDE The Arduino IDE is a software development environment that can be downloaded for free to your own PC and that contains the entire software package needed for your own microcontroller projects. You write your programs ('apps') with the IDE’s editor in the C programming language. You translate them into the bits and bytes that the microcontroller understands using the Arduino IDE's built-in compiler, and then load them into the microcontroller's memory on the Elektor Arduino MCCAB Nano Training Board via a USB cable. Query or control external sensors, motors or assemblies In addition to an Arduino Nano microcontroller module, the Elektor Arduino Nano MCCAB Training Board contains all the components required for the exercises, 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 Elektor Arduino Nano MCCAB Training Board Arduino Nano Book: Microcontrollers Hands-on Course for Arduino Starters

Read (+) (–)

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

Read (+) (–)

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

Read (+) (–)

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

Read (+) (–)

This USB Stick contains more than 300 Arduino-related articles published in Elektor Magazine. The content includes both background articles and projects on the following topics: Software & hardware development: Tutorials on Arduino software development using Arduino IDE, Atmel Studio, Shields, and essential programming concepts. Learning: The Microcontroller Bootcamp offers a structured approach to programming embedded systems. Data acquisition & measurement: Projects such as a 16-bit data logger, lathe tachometer, and an AC grid analyzer for capturing and analyzing real-time signals. Wireless communication: Learn how to implement wireless networks, create an Android interface, and communicate effectively with microcontrollers. Robotics and automation: This covers the Arduino Nano Robot Controller, supporting boards for automation, and explores various Arduino shields to enhance functionality. Self-build projects: Unique projects such as laser projection, Numitron clock and thermometer, ELF receiver, Theremino, and touch LED interfaces highlight creative applications. Whether you're a beginner or an experienced maker, this collection is a valuable resource for learning, experimenting, and pushing the boundaries of Arduino technology.

Read (+) (–)