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Design IoT Projects with Raspberry Pi, Arduino and ESP32 The Internet of Things (IoT) is becoming a major application area for embedded systems. As a result, more and more people are becoming interested in learning about embedded design and programming. Technical colleges and universities are moving away from legacy 8 and 16-bit microcontrollers and are introducing 32-bit embedded microcontrollers to their curriculums. Many IoT applications demand precision, high processing power, and low power consumption. Produced by IBM, Node-RED is an open-source visual editor for wiring the Internet of Things. Node-RED comes with a large number of nodes to handle a multitude of tasks. The required nodes are selected and joined together to perform a particular task. Node-RED is based on flow type programming where nodes are configured and joined together to form an application program. There are nodes for performing complex tasks, including web access, Twitter, E-mail, HTTP, Bluetooth, MQTT, controlling GPIO ports, etc. One particularly nice aspect of Node-RED is that the programmer does not need to learn how to write complex programs. For example, an email can be sent by simply joining nodes together and writing only a few lines of code. The aim of this book is to teach how Node-RED can be used in projects. The main hardware platform used with most of the projects in this book is Raspberry Pi 4. Chapters are included to show how Node-RED can be also be used with Arduino Uno, ESP32 DevKitC, and the ESP8266 NodeMCU microcontroller development boards.

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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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From basics to flows for sensors, automation, motors, MQTT, and cloud services This book is a learning guide and a reference. Use it to learn Node-RED, Raspberry Pi Pico W, and MicroPython, and add these state-of-the-art tools to your technology toolkit. It will introduce you to virtual machines, Docker, and MySQL in support of IoT projects based on Node-RED and the Raspberry Pi Pico W. This book combines several elements into a platform that powers the development of modern Internet of Things applications. These elements are a flow-based server, a WiFi-enabled microcontroller, a high-level programming language, and a deployment technology. Combining these elements gives you the tools you need to create automation systems at any scale. From home automation to industrial automation, this book will help you get started. Node-RED is an open-source flow-based development tool that makes it easy to wire together devices, APIs, and online services. Drag and drop nodes to create a flowchart that turns on your lights at sunset or sends you an email when a sensor detects movement. Raspberry Pi Pico W is a version of the Raspberry Pi Pico with added 802.11n Wi-Fi capability. It is an ideal device for physical computing tasks and an excellent match to the Node-RED. Quick book facts Project-based learning approach. Assumes no prior knowledge of flow-based programming tools. Learn to use essential infrastructure tools in your projects, such as virtual machines, Docker, MySQL and useful web APIs such as Google Sheets and OpenWeatherMap. Dozens of mini-projects supported by photographs, wiring schematics, and source code. Get these from the book GitHub repository. Step-by-step instructions on everything. All experiments are based on the Raspberry Pi Pico W. A Wi-Fi network is required for all projects. Hardware (including the Raspberry Pi Pico W) is available as a kit. Downloads GitHub

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From basics to flows for sensors, automation, motors, MQTT, and cloud services This book is a learning guide and a reference. Use it to learn Node-RED, Raspberry Pi Pico W, and MicroPython, and add these state-of-the-art tools to your technology toolkit. It will introduce you to virtual machines, Docker, and MySQL in support of IoT projects based on Node-RED and the Raspberry Pi Pico W. This book combines several elements into a platform that powers the development of modern Internet of Things applications. These elements are a flow-based server, a WiFi-enabled microcontroller, a high-level programming language, and a deployment technology. Combining these elements gives you the tools you need to create automation systems at any scale. From home automation to industrial automation, this book will help you get started. Node-RED is an open-source flow-based development tool that makes it easy to wire together devices, APIs, and online services. Drag and drop nodes to create a flowchart that turns on your lights at sunset or sends you an email when a sensor detects movement. Raspberry Pi Pico W is a version of the Raspberry Pi Pico with added 802.11n Wi-Fi capability. It is an ideal device for physical computing tasks and an excellent match to the Node-RED. Quick book facts Project-based learning approach. Assumes no prior knowledge of flow-based programming tools. Learn to use essential infrastructure tools in your projects, such as virtual machines, Docker, MySQL and useful web APIs such as Google Sheets and OpenWeatherMap. Dozens of mini-projects supported by photographs, wiring schematics, and source code. Get these from the book GitHub repository. Step-by-step instructions on everything. All experiments are based on the Raspberry Pi Pico W. A Wi-Fi network is required for all projects. Hardware (including the Raspberry Pi Pico W) is available as a kit. Downloads GitHub

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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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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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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 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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Ready-to-use devices and self-built Arduino nodes in the 'The Things Network' LoRaWAN has developed excellently as a communication solution in the IoT. The Things Network (TTN) has contributed to this. The Things Network was upgraded to The Things Stack Community Edition (TTS (CE)). The TTN V2 clusters were closed towards the end of 2021. This book shows you the necessary steps to operate LoRaWAN nodes using TTS (CE) and maybe extend the network of gateways with an own gateway. Meanwhile, there are even LoRaWAN gateways suitable for mobile use with which you can connect to the TTN server via your cell phone. The author presents several commercial LoRaWAN nodes and new, low-cost and battery-powered hardware for building autonomous LoRaWAN nodes. Registering LoRaWAN nodes and gateways in the TTS (CE), providing the collected data via MQTT and visualization via Node-RED, Cayenne, Thingspeak, and Datacake enable complex IoT projects and completely new applications at very low cost. This book will enable you to provide and visualize data collected with battery-powered sensors (LoRaWAN nodes) wirelessly on the Internet. You will learn the basics for smart city and IoT applications that enable, for example, the measurement of air quality, water levels, snow depths, the determination of free parking spaces (smart parking), and the intelligent control of street lighting (smart lighting), among others.

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