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Learn programming for Alexa devices, extend it to smart home devices and control the Raspberry Pi The book is split into two parts: the first part covers creating Alexa skills and the second part, designing Internet of Things and Smart Home devices using a Raspberry Pi. The first chapters describe the process of Alexa communication, opening an Amazon account and creating a skill for free. The operation of an Alexa skill and terminology such as utterances, intents, slots, and conversations are explained. Debugging your code, saving user data between sessions, S3 data storage and Dynamo DB database are discussed. In-skill purchasing, enabling users to buy items for your skill as well as certification and publication is outlined. Creating skills using AWS Lambda and ASK CLI is covered, along with the Visual Studio code editor and local debugging. Also covered is the process of designing skills for visual displays and interactive touch designs using Alexa Presentation Language. The second half of the book starts by creating a Raspberry Pi IoT 'thing' to control a robot from your Alexa device. This covers security issues and methods of sending and receiving MQTT messages between an Alexa device and the Raspberry Pi. Creating a smart home device is described including forming a security profile, linking with Amazon, and writing a Lambda function that gets triggered by an Alexa skill. Device discovery and on/off control is demonstrated. Next, readers discover how to control a smart home Raspberry Pi display from an Alexa skill using Simple Queue Service (SQS) messaging to switch the display on and off or change the color. A node-RED design is discussed from the basic user interface right up to configuring MQTT nodes. MQTT messages sent from a user are displayed on a Raspberry Pi. A chapter discusses sending a proactive notification such as a weather alert from a Raspberry Pi to an Alexa device. The book concludes by explaining how to create Raspberry Pi as a stand-alone Alexa device.

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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. Wat is Edge-AI nu eigenlijk?Intelligentie naar het apparaat brengen Maak kennis met Edge Impulse StudioEenvoudig Edge-AI modellen bouwen en implementeren Keyword spotting met Edge ImpulseVerzamelen, trainen en implementeren Slimme apparaten bedienen via spraakbesturing met de Nordic Thingy:53 Sleutelbegrippen voor het begrijpen van Edge AI en Machine Learning Snelcursus: Aan de slag met Edge ImpulseLeer een ML-model te verzamelen, trainen en implementeren met de Arduino Nano 33 BLE Sense Een nieuw hoofdstuk voor ArduinoVan hobbyboard tot Edge computing-krachtpatser Aan de slag met objectdetectie op edge-apparaten Detectie van defecten op printplatenComputer Vision met de Raspberry Pi AI op maat maken voor de kleinste apparaten Optimalisatie van het energieverbruik in batterijgevoede Edge-AI apparaten AI ToasterWanneer Edge-AI en ontbijt samenkomen Thundercomm Rubik Pi 3Raspberry Pi ervaring in combinatie met Edge AI Leiderschap, Embedded ML en de Edge-revolutie Vision language models voor EdgeModel-cascadering voor betere betrouwbaarheid Maak kennis met Edge ImpulseVragen van de Elektor-community Projectupdate #5: Energiemeter op basis van ESP32Edge-AI gebruiken voor herkenning van huishoudelijke verbruikers Bewegingsherkenning met anomalie-detectieEen uitgebreide training Slim ventilatiesysteem: integratie van geluids- en omgevingsgegevensEen machine learning toepassing met dubbele MCU voor geautomatiseerde bediening van ramen en lamellen Spraakbesturing voor oordopjes en headsets Edge-AI: de volgende generatie apparaten mogelijk maken

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The FNIRSI GC-03 is a multifunctional radiation detector designed for professional nuclear radiation measurement in everyday environments such as the home, office, car, and outdoors. Equipped with a 2.4-inch high-definition color display, it provides real-time monitoring of nuclear radiation as well as electric and magnetic field strength. For added safety, the device features three alarm modes: audible alert, vibration, and visual light warning. Features 3-in-1 Detection: Monitors electric, magnetic, and nuclear radiation with one device. High-Precision GM Tube: Accurately detects gamma, X-rays, and hard beta radiation with low power consumption. Real-Time Curve + 50 Alarm Records: Tracks radiation trends and stores alarm history for easy review. Custom Triple Alarms: Supports visual, audible, and vibration alerts with adjustable thresholds. Long Battery Life: 1500 mAh battery for extended and reliable field use. Specifications Nuclear Radiation Range: 0.01μSv/h-999.99μSv/h Accuracy: 0.01μSv/h Electric Field Range: 1V/m-1999V/m Accuracy: 1V/m Magnetic Field Range: 0.01μT-99.99μT Accuracy: 0.01μT Radiation Power 0.2-1000mW/m² Detection Radiation Type Ionizing radiation (gamma rays, etc.) Detector Energy compensation GM tube (Geiger counter tube) Dose Current Rate 0.00-10000μSv/h (10mSv/h) Cumulative Dose Equivalent 0.00μSv-500.0mSv Energy Range 48keV-1.5MeV ≤ ±30% (for 137Cs-) Sensitivity 80CPM/μSv Dose Unit μSv/h, uGy/h, mR/h, CPS, CPM Alarm Mode Light, vibration, sound Display 2.4-inch color screen Backlight Brightness Adjustable Power Supply USB-C (5 V/1 A) Battery 1500 mAh Languages English, Chinese Dimensions 138 x 63 x 32 mm Weight 141 g Included 1x FNIRSI GC-03 Radiation Detector 1x USB cable 1x Manual Downloads Manual Firmware v1.0.4

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Praktische Anwendungen und Projekte mit Arduino, ESP32 und RP2040 Tauchen Sie ein in die faszinierende Welt der Regelungstechnik mit Arduino und ESP32! Dieses Buch bietet Ihnen einen praxisnahen Einstieg in die klassischen und modernen Methoden der Regelung, darunter PID-Regler, Fuzzy-Logik und Sliding-Mode-Regler. Im ersten Teil lernen Sie die Grundlagen der beliebten Arduino-Controller, wie den Arduino Uno und den ESP32, sowie die Integration von Sensoren für Temperatur- und pH-Messung (NTC, PT100, PT1000, pH-Sensor). Sie erfahren, wie diese Sensoren in verschiedenen Projekten eingesetzt werden und wie Sie Daten auf einem Nextion TFT-Display visualisieren. Weiter geht es mit der Einführung in Stellglieder wie MOSFET-Schalter, H-Brücken und Solid-State-Relais, die zur Steuerung von Motoren und Aktoren verwendet werden. Sie lernen, Regelstrecken zu analysieren und zu modellieren, einschließlich PT1- und PT2-Regelungen. Der Schwerpunkt des Buches liegt auf der Implementierung von Fuzzy- und PID-Reglern zur Regelung von Temperatur und DC-Motoren. Dabei werden sowohl der Arduino Uno als auch der ESP32 eingesetzt. Zudem wird der Sliding-Mode-Regler vorgestellt. Im vorletzten Kapitel erkunden Sie die Grundlagen neuronaler Netze und lernen, wie maschinelles Lernen auf einem Arduino eingesetzt werden kann. Im letzten Kapitel gibt es noch ein praktisches Beispiel für einen Fuzzy-Regler zur Stromeinspeisung ins Hausnetz. Dieses Buch ist die perfekte Wahl für Ingenieure, Studierende und Elektroniker, die ihre Projekte mit innovativen Regelungstechniken erweitern möchten.

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A Practical Guide to AI, Python, and Hardware Projects Welcome to your BeagleY-AI journey! This compact, powerful, and affordable single-board computer is perfect for developers and hobbyists. With its dedicated 4 TOPS AI co-processor and a 1.4 GHz Quad-core Cortex-A53 CPU, the BeagleY-AI is equipped to handle both AI applications and real-time I/O tasks. Powered by the Texas Instruments AM67A processor, it offers DSPs, a 3D graphics unit, and video accelerators. Inside this handbook, you‘ll find over 50 hands-on projects that cover a wide range of topics—from basic circuits with LEDs and sensors to an AI-driven project. Each project is written in Python 3 and includes detailed explanations and full program listings to guide you. Whether you‘re a beginner or more advanced, you can follow these projects as they are or modify them to fit your own creative ideas. Here’s a glimpse of some exciting projects included in this handbook: Morse Code Exerciser with LED or BuzzerType a message and watch it come to life as an LED or buzzer translates your text into Morse code. Ultrasonic Distance MeasurementUse an ultrasonic sensor to measure distances and display the result in real time. Environmental Data Display & VisualizationCollect temperature, pressure, and humidity readings from the BME280 sensor, and display or plot them on a graphical interface. SPI – Voltmeter with ADCLearn how to measure voltage using an external ADC and display the results on your BeagleY-AI. GPS Coordinates DisplayTrack your location with a GPS module and view geographic coordinates on your screen. BeagleY-AI and Raspberry Pi 4 CommunicationDiscover how to make your BeagleY-AI and Raspberry Pi communicate over a serial link and exchange data. AI-Driven Object Detection with TensorFlow LiteSet up and run an object detection model using TensorFlow Lite on the BeagleY-AI platform, with complete hardware and software details provided.

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Build your own AI microcontroller applications from scratch The MAX78000FTHR from Maxim Integrated is a small development board based on the MAX78000 MCU. The main usage of this board is in artificial intelligence applications (AI) which generally require large amounts of processing power and memory. It marries an Arm Cortex-M4 processor with a floating-point unit (FPU), convolutional neural network (CNN) accelerator, and RISC-V core into a single device. It is designed for ultra-low power consumption, making it ideal for many portable AI-based applications. This book is project-based and aims to teach the basic features of the MAX78000FTHR. It demonstrates how it can be used in various classical and AI-based projects. Each project is described in detail and complete program listings are provided. Readers should be able to use the projects as they are, or modify them to suit their applications. This book covers the following features of the MAX78000FTHR microcontroller development board: Onboard LEDs and buttons External LEDs and buttons Using analog-to-digital converters I²C projects SPI projects UART projects External interrupts and timer interrupts Using the onboard microphone Using the onboard camera Convolutional Neural Network

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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. Autonome sensor-nodeLoRa-gebaseerde datatransmissie, voeding met zonnecellen Elektor eXpansion Board v1.0voor ESP32S3 en andere XIAO-controllerboards Modeltrein met camerainbouw van een ESP32 CAM-module Breedbandige magnetische lange golf-antenneontvang meerdere kanalen zonder afstemmen TensorFlow Lite op kleine microcontrollersvanuit het standpunt van een (absolute) beginner Een hub voor RS-422- en RS-485-apparatende bus is de ster! RF-sondemet LED-staafdiagram Alle begin......bekijkt meer opampschakelingen Open VarioEen Open-Source Multifunctie Variometer voor Paragliden Uit het leven gegrepenover de vanzelfsprekendheid der dingen AI-gebaseerde watermeter-uitlezing (2)koppel uw oude watermeter met het IoT! Slimme landbouwdetectie van ongedierte op basis van machine learning met IoT-connectiviteit Waarom Anybus CompactCom de ideale keuze is voor embedded industriële communicatie Communicatie standaard IQRFBetrouwbaarheid voor draadloze, low-rate Mesh-netwerken met verlies Constructie van een slimme landbouwrobotbelangrijkste technische overwegingen en uitdagingen Audio-notchfilter met instelbare frequentieuniversele oplossing voor het onderdrukken van frequenties in audiotoepassingen Het LeoINAGPS-systeemnuttige informatie over uw elektrische voertuig LoRa-node op zonne-energieeenmodulaire, compacte en veelzijdige IoT-oplossing AWS voor Arduino en co. (2)data versturen met AWS IoT ExpressLink Project 2.0correcties, updates en brieven van lezers 2024: een AI-odysseedesktop- versus embedded accelerators: enkele opties ESP32-bereiksuitbreidingeen eenvoudige antenne-modificatie WoTS 2024World of Industry, Technology & Science biedt oplossingen Metafas @ WoTS 2024Smart thinking in printed electronics Hansamatrix @ WoTS 2024 Value Procurement Centre @ WoTS 2024Omdat niet alles in Nederland kan! PCBWay @ WoTS 2024 GW Instek @ WoTS 2024 Rohde & Schwarz @ WoTS 2024 Unis Group @ WoTS 2024 Eurocircuits @ WoTS 2024Jouw Pad naar Uitmuntendheid in Elektronica Productie

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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

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Temporary Delay in the Delivery of Unitree Robots Like many other suppliers, we are currently experiencing delays in the delivery of Unitree robots. A shipment from our supplier is currently held in customs, which has unfortunately led to later-than-planned deliveries for previously placed orders. We are actively working with our supplier to resolve this issue and expect more clarity soon, but at this time, we cannot provide any guarantees. Additionally, a new shipment is already on its way, though it will take some time to arrive. Since other suppliers are facing similar challenges, switching to a different provider is unlikely to result in a faster solution. Our top priority remains fulfilling existing orders. If you have any questions or would like to update your order, please do not hesitate to contact our customer service team. We will keep you informed of any further developments. Unitree Go2 series consists of quadruped robots for the research & development of autonomous systems in the fields of human-robot interaction (HRI), SLAM & transportation. Due to the four legs, as well as the 12DOF, this robot can handle a variety of different terrains. The Go2 comes with a perfected drive & power management system, which enables a speed (depending on the version) of up to 3.7 m/s or 11.88 km/h with an operating time of up to 4 hours. Furthermore, the motors have a torque of 45 N.m at the body/thighs and at the knees, which also allow jumps or backflips. Features Super Recognition System: 4D LIDAR L1 Max Running Speed: approx. 5 m/s Peak Joint Torque: approx. 45 N.m Wireless Module: WiFi 6/Bluetooth/4G Ultra-long battery Endurance: approx. 2-4 h (long battery life measured in real life) Intelligent Side-follow System: ISS 2.0 Specifications Tracking module: Remote-controlled or automatic tracking Front camera: Image tansmission Resolution 1280x720, FOV 120°, Ultra wide angle lens deliver rich clarity Front lamp: Brightly lights the way ahead 4D LiDAR L1: 360°x90° omnidirectional ultra-wide-angle scanning allows automatic avoidance with small blind spot and stable operation 12 knee joint motors: Strong and powerful, Beautiful and simple, Brandy new visual experience Intercom microphone: Effective communication with no scenario restrictions Self-retracting strap: Easy to carry and load things More stable, more powerful with advanced devices: 3D LiDAR, 4G ESIM Card, WiFi 6 with Dual-band, Bluetooth 5.2 for stable connection and remote control Powerful Computing Core: Motion controller, High-performance ARM processor, Improved Al algorithm processor, External ORIN NX/NANO Smart battery: Standard 8000 mAh battery, Long-endurance 15000 mAh battery, Protection from over-temp, overcharge and short-circuit Speaker for music play: Listen to music as your pleasure Unitree Go2 Variants The Go2 impresses not only with its technical capabilities, but also with a modern and slim design that gives it a futuristic look and makes it a real eye-catcher. The Go2 Air is specially designed for demos and presentations. With its basic features, it offers a solid basis for demonstrating the movement capabilities and functionality of a four-legged robot. Important: The Go2 Air is delivered without a controller. This can be purchased optionally. With a powerful 8-core high-performance CPU, the Pro and Edu offer impressive computing power required for complex tasks and demanding calculations. This enables faster and more efficient data processing and makes the Pro and Edu a reliable partner for your projects. From the Edu version onwards, the Go2 is programmable and opens up endless possibilities for developing and researching your own robotics applications. The Go2 is also able to handle a step height of up to 14 cm. This makes it an ideal tool for research, education and entry into the world of robotics. The Go2 Edu comes with a remote controller that gives you easy and intuitive control. You also get a docking station with impressive computing power of 100 TOPS, which is equipped with powerful AI algorithms and offers you technical support. Go2 Edu is equipped with a powerful 15000 mAh battery that gives it an impressive runtime of up to 4 hours. This long operating time allows the robot to carry out longer exploration missions and complete demanding tasks. Model Comparison Air Pro Edu/Edu Plus Dimensions (standing) 70 x 31 x 40 cm 70 x 31 x 40 cm 70 x 31 x 40 cm Dimensions (crouching) 76 x 31 x 20 cm 76 x 31 x 20 cm 76 x 31 x 20 cm Material Aluminium alloy + High strength engineering plastic Aluminium alloy + High strength engineering plastic Aluminium alloy + High strength engineering plastic Weight (with battery) about 15 kg about 15 kg about 15 kg Voltage 28~33.6 V 28~33.6 V 28~33.6 V Peaking capacity about 3000 W about 3000 W about 3000 W Payload ≈7 kg (MAX ~ 10 kg) ≈8 kg (MAX ~ 10 kg) ≈8 kg (MAX ~ 12 kg) Speed 0~2.5 m/s 0~3.5 m/s 0~3.7 m/s (MAX ~ 5 m/s) Max Climb Drop Height about 15 cm about 16 cm about 16 cm Max Climb Angle 30° 40° 40° Basic Computing Power N/A 8-core High-performance CPU 8-core High-performance CPU Aluminum knee joint motor 12 set 12 set 12 set Intra-joint circuit (knee) ✓ ✓ ✓ Joint Heat Pipe Cooler ✓ ✓ ✓ Range of Motion Body: −48~48° Body: −48~48° Body: −48~48° Thigh: −200°~90° Thigh: −200°~90° Thigh: −200°~90° Shank: −156°~−48° Shank: −156°~−48° Shank: −156°~−48° Max Torque N/A about 45 N.m about 45 N.m Super-wide-angle 3D LiDAR ✓ ✓ ✓ Wireless Vector Positioning Tracking Module N/A ✓ ✓ HD Wide-angle Camera ✓ ✓ ✓ Foot-end force sensor N/A N/A ✓ Basic Action ✓ ✓ ✓ Auto-scaling strap N/A ✓ N/A Upgraded Intelligent OTA ✓ ✓ ✓ RTT 2.0 Image Transmission ✓ ✓ ✓ App Basic Remote Control ✓ ✓ ✓ App Data Viewing ✓ ✓ ✓ App Graphical Programme ✓ ✓ ✓ Front Lamp (3 W) ✓ ✓ ✓ WiFi 6 with Dual-band ✓ ✓ ✓ Bluetooth 5.2/4.2/2.1 ✓ ✓ ✓ 4G Module N/A CN/GB CN/GB Voice Function N/A ✓ ✓ Music Playback N/A ✓ ✓ ISS 2.0 Intelligent side-follow system N/A ✓ ✓ Intelligent detection and avoidance ✓ ✓ ✓ Secondary development N/A N/A ✓ Manual controller Optional Optional ✓ High computing power module N/A N/A Edu: 40 TOPS computing power Edu Plus: 100 TOPS computing power NVIDIA Jetson Orin (optional) Smart Battery Standard (8000 mAh) Standard (8000 mAh) Long endurance (15000 mAh) Battery Life 1-2 h 1-2 h 2-4 h Charger Standard (33.6 V, 3.5 A) Standard (33.6 V, 3.5 A) Fast charge (33.6 V, 9 A) Included 1x Unitree Go2 Pro 1x Unitree Go2 Battery (8000 mAh) Downloads Documentation iOS/Android apps GitHub

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Le téléchargement intégral de ce numéro est disponible pour nos membres GOLD et GREEN sur le site Elektor Magazine ! Pas encore membre ? Cliquez ici. qu’est-ce que l’edge AI ?L’IA, intégrée à l’appareil découvrez Edge Impulse StudioConcevez et déployez facilement des modèles d’IA en périphérie détection de mots-clés avec Edge ImpulseCollecter, entraîner et déployer contrôle d’appareils par commande vocale avec le Nordic Thingy:53 Termes clés pour comprendre l’edge AI et le machine learning cours accéléré : démarrez avec Edge ImpulseApprenez à collecter, entraîner et déployer un modèle ML avec l’Arduino Nano 33 BLE Sense un nouveau chapitre pour ArduinoD’une carte pour amateurs à une plateforme d’edge computing premiers pas avec la détection d’objets sur des appareils edge détection de défauts sur circuits imprimésVision par ordinateur avec Raspberry Pi adapter l’IA aux appareils les plus compacts optimiser l’efficacité énergétique des appareils edge AI alimentés sur batterie grille-pain intelligentL’IA qui reconnaît le toast parfait Thundercomm Rubik Pi 3Raspberry Pi et l’edge AI, enfin réunis Leadership, ML embarqué et révolution de l’IA en périphérie modèles vision-langage en périphérieCascade de modèles pour une meilleure fiabilité découvrez Edge ImpulseQuestions de la communauté Elektor mise à jour du projet n°5 : Compteur d’énergie ESP32Utiliser l’Edge AI pour identifier les charges domestiques reconnaissance de mouvements avec détection d’anomaliesUn tutoriel détaillé système de ventilation intelligent : fusion des données sonores et environnementalesUtilisation d’un microcontrôleur double-cœur et du ML pour l’automatisation des fenêtres et persiennes intégrer la commande vocale aux écouteurs et aux casques l'IA en périphérie : au cœur des appareils de demain

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. The ESP-BLASTA Mini ESP32 Rocket Drone That Flies 100 km/h+ Wireless Workshop (1)Radio Modules Unlocked: 433 MHz CC1101 Sub-GHz Transceiver AM TransmitterWith Square/Sine Wave Generator on Raspberry Pi Pico STM32Cube Innovation ChallengeCompete with Your Best STM32C5 Design CoffeeCallerHow a Long Hallway Led to a Custom Mesh-Networked PCB AudiotronicsTotal Harmonic Distortion Elektor at 65Projects from Septembers and Octobers Past Bluetooth Channel Sounding for Asset TrackingCentimeter-Level Precision Ranging for Next-Generation IoT 2026: An AI OdysseyQuantum Computing Is Not the Next GPU Protecting the Cloud Demands Security at the Edge First Experiences with the HackRF ProPractical Tests with the New SDR Hardware Modem Upgrade from GPRS/2G to LTE/4GUsing a Wireless Alarm Control Panel as an Example Loop Antenna with RF BricksPart 1: A DIY Shortwave Antenna with Adjustable Directivity Internet Radio to AM ConverterUsing an ESP32-S3 as Transmitter Err-lectronics mioty — An OverviewFraunhofer’s Approach to LPWAN Workbench WisdomPractical Tips from Experts Walter, the Compact IoT ModulePart 2: Accessing Weather and Data Services

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DIY LiPo Supercharger KitFrom Handcrafted to Mass Market Elektor @ 60Reflections on Six Decades of Electronics Siglent Bench Multimeter SDM3045X DC Current-Sense ClampHall Sensor + Ferrite Core + Arduino Soldering Station 2021Easy to build! Hands On the Parallax Propeller 2Part 2: The Development Environment and Code Wi-Fi for LoRa SwitchIntegrated in Home Assistant with ESPHome Do Not Fear the Cellular Module! Tracking Time with ESP32 and TogglWorking with the M5Stack Get to Know the Raspberry Pi Pico Board and RP2040 MicroPython for MicrocontrollersSmall-Format Screens 12-to-200-V DC/DC Converter for Valve Amplifiers Heat SeekerThe Seek Shot Pro Thermal Imaging Camera Object-Oriented Programming: A Short Primer Using C++ HomeLab ToursHome Lab and an Analogue Synthesiser by Kurt Diedrich Java on the Raspberry PiPart 1: GPIOs DIP SwitchesPeculiar Parts, the series Project 2.0Corrections, Updates and Readers’ Letters Whose Product Is It Anyway?Right to Repair Gains Momentum From Life's ExperienceThe Great Book of Blunders Micro-ProfessorLearning Assembly Language on a Z80 Starting out in ElectronicsEasier Than Imagined! Even When It Is About Capacitors HexadokuThe Original Elektorized Sudoku

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