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This bundle gives you everything you need to get started right away with the XIAO ESP32-C3 development board. Learn the fundamentals of the ESP32-C3 and build practical projects with Wi-Fi, Bluetooth, sensors, displays, PWM, Deep Sleep, and much more. Book: Build Smart Projects with the XIAO ESP32-C3 Board The XIAO ESP32-C3 board combines the ultra-compact form factor of the XIAO series with the full capabilities of the ESP32-C3 chip, including integrated Wi-Fi and Bluetooth 5.0. This book is a comprehensive, hands-on guide to getting the most out of this powerful yet affordable development board. The author takes readers from the fundamentals to advanced projects. Starting with LED blinking and dimming, the book progresses to ADC and PWM for precise sensor interfacing and PWM-controlled lighting effects before moving on to building practical, real-world applications, including: A Wi-Fi weather station with an OLED display and real-time online weather data An ultrasonic parking assistant with audible feedback A refrigerator monitoring probe with climate sensing and Deep Sleep for years of battery operation A retro Pong game controlled by a touch-free sensor A microphone-based party app that responds to claps And much more: lighting control, reaction-time measurement, mains frequency analysis, soil moisture sensing, ambient LED lighting, and 7-segment displays Seeed Studio XIAO ESP32C3 Seeed Studio XIAO ESP32C3 has equipped a highly-integrated ESP32-C3 chip, built around a 32-bit RISC-V chip processor with a four-stage pipeline that operates at up to 160 MHz. The board equips highly-integrated ESP32-C3 SoC. The chip has been installed with a complete 2.4 GHz Wi-Fi subsystem which means it supports Station mode, SoftAP mode, SoftAP & Station mode, and promiscuous mode for multiple Wi-Fi applications. It works under an ultra-low power state, also supporting features of Bluetooth 5 and Bluetooth mesh. There are 400 KB SRAM & 4 MB Flash on the chip, allowing for more programming space, and bringing more possibilities to the IoT control scenarios. Applications Internet of Things Wearable devices Health monitoring Education Low-Power networking Rapid prototyping Specifications Processor ESP32-C3 SoC RISC-V single-core 32-bit chip processor with a four-stage pipeline that operates at up to 160 MHz Wireless Complete 2.4GHz Wi-Fi subsystem Bluetooth Low Energy 5.0/ Bluetooth Mesh On-chip Memory 400 KB SRAM & 4 MB Flash Interface 1x UART, 1x I²C, 1x SPI, 11x GPIO (PWM), 4x ADC 1x Reset button, 1x Boot button Power (Typ.) Max 3.3 V Output Current: 500 mA Test Condition: BAT Pin Input @ 3.8 V Source Capability: 3 A Charging current: 380 mA(Fast) / 40 mA(Trickle) Input voltage (VIN): 5 VInput voltage (BAT): 3.7 V Deep Sleep Power Consumption Deep Sleep Mode: 44 μA Wi-Fi Enabled Power Consumption Active Mode: 75 mA Modem-sleep Mode: 25 mA Light-sleep Mode: 4 mA BLE Enabled Power Consumption Modem-sleep Mode: 27 mA Light-sleep Mode: 10 mA Dimensions 21 x 17.8 mm Included 1x Seeed Studio XIAO ESP32C3 1x Antenna 2x 7-pin header Downloads Wiki Datasheet This bundle contains: Book: Build Smart Projects with the XIAO ESP32-C3 Board (normal price: €35) Board: Seeed Studio XIAO ESP32C3 (normal price: €10)

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

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This bundle 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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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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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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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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Build Smart Applications with Raspberry Pi, Arduino, and ESP32 Discover how easy and exciting mobile app development can be with MIT App Inventor. This hands-on guide takes you from basic concepts to building real-world mobile applications using a simple visual programming approach—no prior coding experience required. You will create IoT and AI-powered apps for Android devices and explore how App Inventor can also be used with iPhones and iPads. Connect your applications to platforms such as Arduino UNO R4 WiFi, ESP32, Raspberry Pi Pico (2)W and Raspberry Pi 5, enabling you to build smart, connected systems. Inside the book, you will learn how to: Build interactive apps using buttons, images, sound, and multimedia Create text-to-speech and speech-recognition applications Develop camera-based and location-aware (GPS) apps Design useful tools such as calculators and educational apps Work with smartphone sensors like accelerometers and light sensors Build AI-powered applications, including voice assistants and image-generation features Send and receive messages, and create communication-based apps Connect mobile apps to hardware using Wi-Fi and Bluetooth Control real devices such as LEDs, motors, and sensors Designed for beginners, students, and hobbyists, this book focuses on learning by doing. By the end, you will have the skills and confidence to create your own innovative applications that interact with both the digital and physical worlds. Start building and turning your ideas into reality.

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Learn how to use the ESP32 Microcontroller and MicroPython programming in your future projects! The project book, written by well-known Elektor author Dogan Ibrahim, holds many software- and hardware-based projects especially developed for the MakePython ESP32 Development Kit. The kit comes with several LEDs, sensors, and actuators. The kit will help you acquire the basic knowledge to create IoT projects. The book’s fully evaluated projects feature all the supplied components. Each project includes a block diagram, a circuit diagram, a full program listing, and a complete program description. Included in the kit 1x MakePython ESP32 development board with LCD 1x Ultrasonic ranging module 1x Temperature and humidity sensor 1x Buzzer module 1x DS18B20 module 1x Infrared module 1x Potentiometer 1x WS2812 module 1x Sound sensor 1x Vibration sensor 1x Photosensitive resistance module 1x Pulse sensor 1x Servo motor 1x USB cable 2x Button 2x Breadboard 45x Jumper wire 10x Resistor 330R 10x LED (Red) 10x LED (Green) 1x Project book (206 pages) 46 Projects in the Book LED Projects Blinking LED Flashing SOS Blinking LED – using a timer Alternately flashing LEDs Button control Changing the LED flashing rate using pushbutton interrupts Chasing-LEDs Binary-counting LEDs Christmas lights (random-flashing 8 LEDs) Electronic dice Lucky day of the week Pulsewidth Modulation (PWM) Projects Generate a 1000-Hz PWM waveform with 50% duty cycle LED brightness control Measuring the frequency and duty cycle of a PWM waveform Melody maker Simple electronic organ Servo motor control Servo motor DS18B20 thermometer Analog To Digital Converter (ADC) Projects Voltmeter Plotting the analog input voltage ESP32 internal temperature sensor Ohmmeter Photosensitive resistance module Digital To Analog Converter (DAC) Projects Generating fixed voltages Generating a sawtooth-wave signal Generating a triangular-wave signal Arbitrary periodic waveform Generating a sinewave signal Generating accurate sinewave signal using timer interrupts Using The OLED Display Seconds counter Event counter DS18B20 OLED based digital thermometer ON-OFF temperature controller Measuring the temperature and humidity Ultrasonic distance measurement Height of a person (stadiometer) Heart rate (pulse) measurement Other Sensors Supplied with the Kit Theft alarm Sound-activated light Infrared obstacle avoidance with buzzer WS2812 RGB LED ring Timestamping temperature and humidity readings Network Programming Wi-Fi scanner Remote control from the Internet browser (using a smartphone or PC) – Web Server Storing temperature and humidity data in the Cloud Low-Power Operation Using a timer to wake up the processor

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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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LoRaWAN, Sigfox, NB-IoT & LTE-M Compared The Internet of Things depends on a critical question. How do you connect devices that must operate for years on tiny batteries, often miles from the nearest power outlet? This Elektor Technical Brief provides a practical guide to the technologies that have become the backbone of long-range, low-power IoT connectivity. Compiled by the Elektor Content Team, this concise technical brief examines the real engineering tradeoffs behind today’s leading Low-Power Wide-Area Network (LPWAN) technologies: LoRaWAN, Sigfox, NB-IoT, and LTE-M. By referencing a wide range of Elektor articles and other online content, this document explains why link budget, noise, bandwidth, and power consumption ultimately determine system performance. From there, it explores the architectures, strengths, limitations, and deployment realities of each major LPWAN technology, helping you understand not just how they work, but when and why to use them. Whether you’re designing smart meters, industrial sensors, agricultural monitoring systems, asset trackers, or connected infrastructure, this guide provides the insights needed to make informed connectivity decisions. Along the way, you’ll discover: Why LPWAN technologies emerged and where they fit in the IoT landscape The RF fundamentals that drive range, reliability, and battery life Details about LoRaWAN, Sigfox, NB-IoT, and LTE-M Practical comparisons of power, coverage, latency, cost, and deployment models Guidance for selecting the right LPWAN technology for your application Emerging trends shaping the future of long-range IoT connectivity Clear, accessible, and grounded in real engineering practice, this Technical Brief helps you move beyond specifications and marketing claims to understand what matters most. If you’re building connected products that need to survive in the field — not just in the lab — this is the LPWAN guide you’ll want at your side. Elektor helped launch the first wave of electronics makers in 1961. Since then, our global community has grown by hundreds of thousands of active members (comprising professional engineers, makers, and students) and more than 500 contributing experts. Every day, we inspire members to design and earn money with electronics.

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