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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 Edu Plus 1x Unitree Go2 Remote Controller 1x Unitree Go2 Battery (15000 mAh) 1x Unitree Docking station with 100 TOPS computing power Downloads Documentation iOS/Android apps GitHub

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. The AlertAlfred AI Security SystemPowered by a Raspberry Pi 5 and the Hailo 8L Module AI in Electronics DevelopmentAn Update After Only One Year Intro to AI AlgorithmsPrompt: Which Algorithms Implement Each AI Tool? Single-Board Computers for Artificial Intelligence ProjectsBackground and Overview From Sensor Data to Machine Learning ModelsGesture Detection with an Accelerometer and Edge Impulse Build a Leaky Integrate-and-Fire Spiking NeuronArtificial Intelligence Without Software ChatGPT for Electronic DesignDoes GPT-4o Do It Any Better? Bringing AI to the Edge with ESP32-P4 Exploring Speech Functions on Raspberry Pi ZeroWhen Overclocking Gives Freedom of Speech The Growing Role of Edge AIA Trend Shaping the Future Unlocking the Power of Edge AIA Conversation with François de Rochebouët of STMicroelectronics A VHDL Clock Made with ChatGPT AI’s Real ImpactSayash Kapoor on “AI Snake Oil” and More The Latest Stuff From BeagleBoardBeagleY-AI, BeagleV-Fire, BeagleMod, BeaglePlay and BeagleConnect Freedom Mosquito Detection Using Open Datasets and Arduino Nicla Vision AI Today and Tomorrow: Insights from Espressif, Arduino, and SparkFun Artificial Intelligence Timeline BeagleY-AIThe Latest SBC for AI Applications AI in FocusPerspectives from the Elektor Community Machine Vision with OpenMVCreate a Soda Can Detector A Conversation with the Digital MindChatGPT vs Gemini Skilling Me Softly with This Bot?Is the AI Revolution in the Electronic Field Failing Due to a Lack of Social Precision?

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Highlights Frequency: 1.5 GHz DANL: -155 dBm Phase Noise: -80 dBc/Hz RBW: 10 Hz Tracking Generator Specifications All-Digital IF Technology Frequency Range from 9 kHz up to 1.5 GHz Min. -161 dBm Displayed Average Noise Level (Typ.) Min. < -98 dBc/Hz @ 10 kHz Offset Phase Noise Level Measurement Uncertainty < 0.8 dB 10 Hz Minimum Resolution Bandwidth Up to 1.5 GHz Tracking Generator Advanced Measurement Functions (Opt.) EMI Filter & Quasi-Peak Detector Kit (Opt.) VSWR Measurement Kit (Opt.) PC Software (Opt.) Optional RF TX/RX Training Kit Optional RF Accessories (Cable, Adaptor, Attenuator, Bridge ...) Complete Connectivity: LAN (LXI), USB Host & Device, GPIB (Opt.) 8 Inch WVGA (800x480) Display Compact Size, Light Weight Design Included 1x Rigol DSA815-TG Spectrum Analyzer 1x Power cord 1x USB cable

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Open-Source-Code mit Arduino IDE und PlatformIO Autonomes Fahren: GPS, Accelerometer, Gyroskop PS3-Controller Mikrocontroller wie der Arduino und Einplatinenrechner wie der Raspberry Pi haben sich zu beliebten Komponenten entwickelt. Dritter im Bunde ist der ESP32 der Firma Espressif. Mikrocontroller dieser Baureihe zeichnen sich durch eine Vielzahl implementierter Funktionen aus, die bei einem Arduino konventioneller Prägung mit einem Atmel-AVR-Mikrocontroller erst mit weiterer Hardware möglich sind. Prominentes Beispiel sind hier die WiFi- und Bluetooth-Funktionalitäten. Gegenüber einem Raspberry Pi zeichnen sie sich durch einen deutlich geringeren Preis aus. Allgemeine Informationen für die Realisierung eines Roboterauto-Projekts mit dem ESP32 sind leicht zu finden. Dabei handelt es sich aber oft nur um Ausführungen zu einem Teilaspekt, ohne inhaltliche oder funktionale Abstimmung. So ist nicht nur die Beschaffung der benötigten Informationen mühselig und zeitaufwändig, sie kann auch außerordentlich fehlerträchtig sein. Ansatzpunkt dieses Buches ist, diese Lücke zu schließen. Es geht auf verschiedene Möglichkeiten eines Chassis ein, vermittelt nötige Kenntnisse und führt schrittweise von einer einfachen Motorsteuerung zu einem komplexen sensor- und sprachgesteuerten Roboterauto. Hacks rund um GPS und eine PlayStation 3 runden die Sache ab. Inhalt Bei der Reihenfolge der Kapitel wurde versucht – beginnend bei der Darstellung von grundlegenden Informationen – über die Lösung einfacher Aufgaben zu etwas anspruchsvolleren Techniken zu führen. Der Mikrocontroller ESP32 Die Software erstellen Die Stromversorgung Rund um die Hardware Das Chassis Der Gleichstrommotor Kabellose Steuerung über WiFi Mit Sensoren Hindernisse erkennen Eine eigene Roboterauto-App Servo und Lichtsensor GPS Accelerometer / Gyroskop PS3-Controller Roboterauto-App Hinweis zur Software Die Dateien haben das Suffix (.cpp). Grund ist die Entwicklung mit PlatformIO. Mit Copy & Paste sollten sie auch in der Arduino-IDE verwendet werden können.

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. For Eyes and Ears Video Output with Microcontrollers (1)Composite Video electronica 2022News from the world’s leading electronics trade show ESP32 CameraSo Simple, It Doesn’t Even Have to Use Wi-Fi ATX Power Supply for Raspberry Pi 32 Ω Headphone AmplifierSimple But High-Quality 3-Chip Solution SDR Radio-Controlled clocksFive Time Signals, Six Displays Starting Out in ElectronicsSpecial Diodes From Life's ExperienceMusings on the Quality of Things Reverse-Engineering a Bluetooth Low Energy LED BadgeHow to Control a BLE Device with a Python Script MakePython ESP32 Development KitEverything in a Box THD Measurement with an Oscilloscope and FFTEasily Calculate the Distortion Factor All-Seeing MachinesThe Technology Behind Today’s Industrial Vision Systems Infographics The Evolution of Voice and Audio Control for Electronic Devices WEEF 2022 in Review FFWD electronica 2022 in ReviewInnovators Did Not Fail to Impress The TubeAn Unusual Tube Amplifier Biomaterial in Electronics: Ready or Not Opera Cake Antenna Switch for HackRF OneConnect Up To Eight Antennas To Your SDR Engineering with Arduino and MoreAn Interview with Author Ashwin Pajankar LiDAR Precision GaugeMeasure up to 12 Meters Audio Signals and the ESP32The ESP-ADF Environment in Practice Elektor Fortissimo-100 Power Amplifier Kit Using Light for Sound EffectsLDR-Based Voltage-Controlled 24 dB/oct Synthesizer Filter Elektor High-Power AF AmplifierThe Loudest of Them All! HomeLab ToursA Volumetric Display Made in Canada Err-lectronicsCorrections, Updates and Readers’ Letters Hexadoku

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Nahezu alle Menschen werden zunehmend mit den Anwendungen der „Künstlichen Intelligenz“ (KI oder AI für engl. Artificial Intelligence) konfrontiert. Musik- oder Videoempfehlungen, Navigationssysteme, Einkaufsvorschläge etc. basieren auf Verfahren, die diesem Bereich zugeordnet werden können. Der Begriff „Künstliche Intelligenz“ wurde 1956 auf einer internationalen Konferenz, dem Dartmouth Summer Research Project geprägt. Eine grundlegende Idee war dabei, die Funktionsweise des menschlichen Gehirns zu modellieren und darauf basierend fortschrittliche Computersysteme zu konstruieren. Bald sollte klar sein, wie der menschliche Verstand funktioniert. Die Übertragung auf eine Maschine wurde nur noch als ein kleiner Schritt angesehen. Diese Vorstellung erwies sich als etwas zu optimistisch. Dennoch sind die Fortschritte der modernen KI, beziehungsweise ihrem Teilgebiet dem sogenannten „Machine Learning“, nicht mehr zu übersehen. Um die Methoden des Machine Learnings näher kennenzulernen, sollen in diesem Buch mehrere verschiedene Systeme zum Einsatz kommen. Neben dem PC werden sowohl der Raspberry Pi als auch der „Maixduino“ in den einzelnen Projekten ihre Fähigkeiten beweisen. Zusätzlich zu Anwendungen wie Objekt- und Gesichtserkennung entstehen dabei auch praktisch einsetzbare Systeme wie etwa Flaschendetektoren, Personenzähler oder ein „Sprechendes Auge“. Letzteres ist in der Lage, automatisch erkannte Objekte oder Gesichter akustisch zu beschreiben. Befindet sich beispielsweise ein Fahrzeug im Sichtfeld der angeschlossenen Kamera, so wird die Information „I see a car!“ über elektronisch erzeugte Sprache ausgegeben. Derartige Geräte sind hochinteressante Beispiele dafür, wie etwa auch blinde oder stark sehbehinderte Menschen von KI-Systemen profitieren können.

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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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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. USB Measurement AdapterTesting Current and Signal Quality of USB Ports 4...20 mA Current Output for Arduino UnoA Reliable, EMI-Insensitive Current Loop Interface Vacuum Cleaner Automatic ControlKeep Your Tools’ Work Area Clean DDS Generator with ATtiny Opamp-Tester V2New PCB – Now Also Suitable for SMDs 550-mW “Lamp” Audio AmplifierGet the Warm Sound of Vacuum Tubes With Ease Fuse GuardMonitoring a Fuse with a Flashing LED HQ RIAA PreamplifierGet the Most Out of Your Vinyl Records! Turntable Speed CalibratorAn Arduino-Based 100–120 Hz Strobe Light Generator Elektor Classics: video buffer/repeater Infrared Remote-Controlled DimmerControl Your Halogen or LED Floor Lamp Effortlessly and With Style How to Use switch…case on Strings in C++/Arduino IDE Magnet FinderWith a Simple Hall-Effect Sensor Raspberry Pi Smart Power ButtonA Solution for Raspberry Pi Up to Model 4 Essential Maker TipsProfessional Insights for Everyday Making Practical Projects with the 555 TimerDC Motor Control and Fast Reaction Challenges Basic AC-Load-On MonitorSave Energy with a Simple Device Power Banks in ParallelA Three-Day Continuous Power Solution VFO Up to 15 MHzAn Implementation With Raspberry Pi Pico Violin Tuner with ATtiny202 Elektor Classics: video amplifier for B/W television sets Capacitance Meter20 pF to 600 nF Quasi-Analog Clockwork Mk IITwo LED Rings for Hours and Minutes You Can Do Anything You Want(with the Arduino Ecosystem at Your Side) Neon Lamp Dice Elektor Classics: RTTY calibrator indicator Inspiring Hardware Designs for Your ESPs Elektor Classics: variable 3 A power supply RGB LEDs with Integrated Control CircuitLight with Precision: ICLEDs Set Standards Experiment: Towards a Mixed-Signal Theremin?Blending Modern Time-of-Flight Sensors With the Timeless XR2206 Analog Generator ESP32 Audio Transceiver Board (Part 1)SD Card WAV File Player Demo Infographics: Circuits and Circuit Design 2025 Small Audio MixerA Simple and Versatile Scalable Design Smart Staircase Light TimerSave More Money on the Energy Bill! Smarten Up Your ShuttersControlling Velux Hardware With an ESP32 and MQTT Solid-State Foot WarmerEnergy-Efficient Comfort Is the M5Stamp Fly Quadcopter the Next Tello? Boosting Wi-Fi Range of the ESP32-C3 SuperMiniA Simple and Effective Antenna Mod ZD-8968 Hot-Air Soldering StationA Budget-Friendly Workhorse or Just Hot Air? Parking Sensor TesterFinding Defects in the PDC System of a Car

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Most people are increasingly confronted with the applications of Artificial Intelligence (AI). Music or video ratings, navigation systems, shopping advice, etc. are based on methods that can be attributed to this field. The term Artificial Intelligence was coined in 1956 at an international conference known as the Dartmouth Summer Research Project. One basic approach was to model the functioning of the human brain and to construct advanced computer systems based on this. Soon it should be clear how the human mind works. Transferring it to a machine was considered only a small step. This notion proved to be a bit too optimistic. Nevertheless, the progress of modern AI, or rather its subspecialty called Machine Learning (ML), can no longer be denied. In this book, several different systems will be used to get to know the methods of machine learning in more detail. In addition to the PC, both the Raspberry Pi and the Maixduino will demonstrate their capabilities in the individual projects. In addition to applications such as object and facial recognition, practical systems such as bottle detectors, person counters, or a “talking eye” will also be created. The latter is capable of acoustically describing objects or faces that are detected automatically. For example, if a vehicle is in the field of view of the connected camera, the information 'I see a car!' is output via electronically generated speech. Such devices are highly interesting examples of how, for example, blind or severely visually impaired people can also benefit from AI systems.

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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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Projects with Thonny-IDE, uPyCraft-IDE, and ESP32 The 'Python' programming language has enjoyed an enormous upswing in recent years. Not least, various single-board systems such as the Raspberry Pi have contributed to its popularity. But Python has also found widespread use in other fields, such as artificial intelligence (AI) or machine learning (ML). It is obvious, therefore, to use Python or the 'MicroPython' variant for use in SoCs (Systems on Chip) as well. Powerful controllers such as the ESP32 from Espressif Systems offer excellent performance as well as Wi-Fi and Bluetooth functionality at an affordable price. With these features, the Maker scene has been taken by storm. Compared to other controllers, the ESP32 has a significantly larger flash and SRAM memory, as well as a much higher CPU speed. Due to these characteristics, the chip is not only suitable for classic C applications, but also for programming with MicroPython. This book introduces the application of modern one-chip systems. In addition to the technical background, the focus is on MicroPython itself. After the introduction to the language, the programming skills learned are immediately put into practice. The individual projects are suitable for use in the laboratory as well as for everyday applications. So, in addition to the actual learning effect, the focus is also on the joy of building complete and useful devices. By using laboratory breadboards, circuits of all kinds can be realized with little effort, turning the testing and debugging of the 100% homebrew projects into an instructive pleasure. The various applications, such as weather stations, digital voltmeters, ultrasound range finders, RFID card readers or function generators, make the projects presented ideally suited for practical courses or subject and study work in the natural sciences, or in science and technology classes.

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ELEKTOR AIDE L'électronique dans des temps difficiles AFFICHAGE D'INFORMATION POUR LA MAISON avec Windows sur le Raspberry Pi DÉMARRER AVEC NODE-RED un outil de programmation open source basé sur des blocs visuels LA tombola d'ÉTÉ d'ELEKTOR GREATSCOTT ! CONSTRUIRE UN SYSTÈME D'ALARME LORA REVUE : ALIMENTATION DE LABORATOIRE JOY-IT RD6006 (KIT) REVUE : INTERFACEBOARD GREATFET ONE QUI N'HONNE PAS LES PETITS – XXL de la boîte à suggestions d'Elektor ANTENNE WIFI EXTERNE 2,4 GHZ POORLUIS CONTRÔLE FACILE DE LA TEMPÉRATURE MARCHE/ARRÊT AVEC CHAPEAU RASPBERRY PI COMMENT PRENDRE DE (BONNES) PHOTOS DÈS L'IMPRESSION... ...et les composants électroniques ? REVUE : NOYAU I2CDRIVER ÉCRAN TACTILE JOY-VIEW 13 DE JOY-IT BOOSTER LED POUR MICROCONTRÔLEURS avec un seul composant ! MACHINE À LAVER À ULTRASONS EXPÉRIMENTALE REVUE : GÉNÉRATEUR DE SIGNAUX JOY-IT JDS2915 générateur de signaux doubles avec compteur de fréquence dans un boîtier métallique PROGRAMMATION DES FEUX DE SIGNALISATION EN LANGAGE PIC ASSEMBLY LED CLIGNOTANT PERMANENT CAPTEUR DE HALL EXPÉRIMENTAL DÉTECTER LES COURT-CIRCUITS AVEC UN MILLIOHM OU ESR MÈTRE KIT PRATIQUE ÉLECTRIQUE SDR PIPELINE DE LABORATOIRES ÉLECTRIQUES KICK-STARTER ÉLECTRIQUE ....eh bien, vous voyez ce que nous voulons dire. AVEZ-VOUS VRAIMENT BESOIN DE TOUT ÇA ??? ici, je passe de nombreuses heures sur des projets électroniques... LABORATOIRE EST OUEST MEILLEUR un aperçu du plus saint des saints, où naissent des projets intéressants BONJOUR LE MONDE! NOUS SOMMES ELEKTOR ET NOUS SOMMES SOCIAUX M4 + A7 + GPU : UNE ÉQUIPE DE RÊVE INÉGALE le nouveau SoC STM32MP1 pour les travaux plus lourds CONFIGURATION DE TEST POUR LE 16F18877 ET AUTRES GRANDES PHOTOS COMMUNICATION INTER-ΜC AVEC LE BUS SPI ET ATMEGA328P SIX VARIANTES DE L'OSCILLATEUR LF/AF (et la capacité de M. Miller) BBC MICRO:BIT oscilloscope absolument minimaliste avec affichage LED FEU DE RUNNING À LED 'KNIGHT RIDER' AVEC ESP32 GÉNÉRATEUR DE SIGNAUX AM LW/MW AVEC ATTINY13 DIPMÈTRE ABSOLUMENT MINIMALISTE SCOOTERS ÉLECTRIQUES BON MARCHÉ quelle est la qualité d'un scooter électrique « homologué » à 300 euros de Lidl ? AIDE AU STATIONNEMENT À ULTRASONS AVEC ARDUINO UNO PÉDALE DE DISTORSION AVEC AMPLI OP ET TUBES DE CHARGE SPATIALE INDISPENSABLE POUR CHAQUE LABORATOIRE D'ÉLECTRONIQUE HEXADOKU IA POUR DÉBUTANTS (2) réseaux de neurones avec Linux et Python

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