Search results for "dragino or lora or gps or hat or for or raspberry or pi"

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

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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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The Elektor LoRa NodeVersatile, long-range, 868-MHz remote control with state feedback and STM32 Inside InteractiveCorrections & Updates || Questions & Answers Analogue Electronics DesignCase Study #1 — Section 2: Preamplifier optimized for MEMS microphone My IoT Button: A Button for the WebPart 1: IoT architecture BASIC for the ESP32 and ESP8266Programming with Annex WiFi RDS ESP32 Doorbell via Telegram“The UPS Man Always Rings Once” Small Circuits RevivalCapita Selecta from the Elektor Project Suggestions Box My First LoRaWANWith Blue Pill, LoRa Breakout Board and The Things Network Elektor Connexions 2003EL “A Strong Supporter of Open Internet”Interview with Wienke Giezeman, Initiator of The Things Network The Meadow F7 BoardA great board for .NET developers Practical ESP32 Multitasking (2)Task priorities Sigfox and the IoT (3)First steps on the network Raspberry Pi Bash Command Cheat Sheet Europe's Most Successful Start-up Accelerator?HighTechXL, Eindhoven, The Netherlands Review: The Enviro+ RPi-HATMeasure air quality with a Raspberry Pi and the Enviro+ HAT Steeped in Electronicsordering components from Ukraine and Russia Review: Andonstar AD407Better than its predecessor? Lab, Sweet LabA glimpse of The Holy Place — no unauthorized entry. Optical Probe for OscilloscopesMeasure brightness fluctuations of lighting systems The 'TABULA' Project - An UpdateTangibles with user feedback How-To Calculate the Prospective Short-Circuit Current or PSCCand choose the proper circuit breaker TMS1000 Series Microcontrollers Peculiar Parts, the series Starting Out in Electronics (2) Easier than imagined! Developer's ZoneTips & Tricks, Best Practices and Other Useful Information Locating Wayward Wires Track and trace concealed and defective cables with ease and certainty Review: Joy-IT DMSO2D72 Portable 3-in-1 Oscilloscope Homebrew PC for the Electronics LabTips on Component Choice and Construction The Elektor ‘Intelekt’ Chess Computer (1981)Tiny Chess 86 ported to the Intel 8088 Beyond ElectronicsPCB Art - Pushing the Limits of Industrial Manufacturing

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Elektor GREEN en GOLD leden kunnen deze uitgave hier downloaden. Nog geen lid? Klik hier om een lidmaatschap af te sluiten. ESP32 Audio Transceiver Board (Deel 2)Draadloze audio-overdracht Inductieve AM-zenderGebruikt Pico's PIO in een Arduino-sketch Navigeren door draadloze protocollen navigerenEen technische gids Satelliettracking met behulp van LoRaHet TinyGS-netwerk brengt gegevens uit de ruimte naar de aarde. 4G-Compatibele SMS afstandsbedieningBedien je apparatuur op afstand Hogesnelheids-probeIngangen met hoge impedantie voor signalen tot 200 MHz Uit het leven gegrepenKafka KrakenSDR Prestatietests met de RP2350Is een upgrade van Raspberry Pi Pico 1 naar versie 2 de moeite waard? Contactloze E-veldmetingen (2)Een laservibrometer voor het beoordelen van de trillingen van het membraan Kristallen en oscillatorenVerbetering van de kristalnauwkeurigheid door gerichte keuze van condensatoren Alle begin......gaat audio! Zelf firmware coderen voor embedded projecten SPECTRAN® V6 MobileModulaire, configureerbare realtime-spectrumanalyzer voor betrouwbare metingen over alle frequentiebereiken De toekomst van AI wordt gesmeed in siliciumEen interview met Anastasiia Nosova Autonome Sensor-Node v2.0 (Systeemarchitectuur)Zonne-energieplatform met geïntegreerde GPS, LoRaWAN en meer Precieze positioneringBluetooth channel sounding getest Testgestuurd ontwikkelen bij het schrijven van firmware Telefoon gestuurde modelautoWi-Fi + ESP32 + Smartphone = Afstandsbediening 2025: Een AI-odysseeAI-redeneermodellen: De gedachtegang-revolutie Zonne-laadregelaar met MPP-tracking (3)Software en Inbedrijfstelling Raspberry Pi Zero Web Streaming CameraDe ZeroTier VPN gebruiken Beste soldeerder van de Beneluxvakmanschap in de schijnwerpers Seminaroverzicht Electronics & ApplicationsLeer, ontdek en netwerk op E&A 2025 Eurocircuits at E&A 2025 E&A gadget 2025: racen over de beursvloer met slimme printplaat op wielenVijf vragen aan Casper van Doorne, ontwerper van de beursgadget Beursgadget E&A bekendontwerp en bestuur je eigen raceauto Vakbeurs E&A is het elektronicaparadijs van de Benelux“Techneuten blijven kinderen” Rohde & SchwarzPioneering Innovation in Test & Measurement Diederik Jekel opent Electronics & Applications

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Elektor Juillet/Août 2021 (PDF)

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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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LoRa with the Raspberry Pi PicoFun with MicroPython What Is RISC-V?And Why the Industry Is So Excited About a New Processing Core! Elektor @ 60Circuits of Summer Past Versatile Power Supply for BreadboardsPositive and Negative Voltages Out of 5 V from USB Raspberry Pi Pico EssentialsSample Chapter: Wi-Fi with the Raspberry Pi Pico Magnetic Levitation the Easy Way Hands On the Parallax Propeller 2Part 3: Smart Pins and Serial Data (UART) Nucleo Boards Programming with the STM32CubeIDESample Chapter: FreeRTOS for the STM32 MCU Developer's ZoneTips & Tricks, Best Practices and Other Useful Information Miniware DT71 Digital Tweezers Wearable Wi-Fi Gadget: ESPHome Does the Job Again Starting out in ElectronicsEasier Than Imagined! This Concludes the Subject of “Capacitors” Simple Sketches Using the Qwiic Ecosystem Java on the Raspberry Pi (Part 2)Controlling GPIOs with a Spring REST Service Raspberry Pi Compute Module 4A Raspberry Pi for Industry Portable, Stand-Alone Air Quality Display for 2.5 µm ParticlesKeep(s) an Eye on Your Health From Life’s ExperienceThe Future Was Better in the Past MicroPython for the ESP32 and FriendsPart 1: Installation and Our First Programs Charge-Coupled Devices in OscilloscopesPeculiar Parts, the series ESD – The Invisible DestroyerComponents Trashed by a Bolt from the Blue Solar Power for Mowing RobotsEcological, Inexpensive, Simple! Europe’s Efforts to Tame Big Tech HexadokuThe Original Elektorized Sudoku

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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Ready to explore the world around you? By attaching the Sense HAT to your Raspberry Pi, you can quickly and easily develop a variety of creative applications, useful experiments, and exciting games. The Sense HAT contains several helpful environmental sensors: temperature, humidity, pressure, accelerometer, magnetometer, and gyroscope. Additionally, an 8x8 LED matrix is provided with RGB LEDs, which can be used to display multi-color scrolling or fixed information, such as the sensor data. Use the small onboard joystick for games or applications that require user input. In Innovate with Sense HAT for Raspberry Pi, Dr. Dogan Ibrahim explains how to use the Sense HAT in Raspberry Pi Zero W-based projects. Using simple terms, he details how to incorporate the Sense HAT board in interesting visual and sensor-based projects. You can complete all the projects with other Raspberry Pi models without any modifications. Exploring with Sense HAT for Raspberry Pi includes projects featuring external hardware components in addition to the Sense HAT board. You will learn to connect the Sense HAT board to the Raspberry Pi using jumper wires so that some of the GPIO ports are free to be interfaced to external components, such as to buzzers, relays, LEDs, LCDs, motors, and other sensors. The book includes full program listings and detailed project descriptions. Complete circuit diagrams of the projects using external components are given where necessary. All the projects were developed using the latest version of the Python 3 programming language. You can easily download projects from the book’s web page. Let’s start exploring with Sense HAT.

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Elektor Juli/Augustus 2021 (PDF)

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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