Search results for "get or started or with or micropython or on or raspberry or pi or pico"

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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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 GREEN en GOLD leden kunnen deze uitgave hier downloaden. Nog geen lid? Klik hier om een lidmaatschap af te sluiten. PIO programmeren op de Raspberry Pi PicoNegen instructies, veel mogelijkheden AI buiten de browser brengenAI-CLI's gebruiken voor het coderen, compileren en valideren van embedded projecten De Scrutiny DebuggerDebuggen, visualiseren en testen van code in Embedded C/C++ Sigfox breakout board (1)Een zelfgebouwde radio BoB Low-Noise voeding (2)Constructie, montage en praktische implementatie Eenvoudige signaalgenerator met de RP2040Analoge en digitale signalen voor ongeveer €10 De toekomst van slimme huizen verkennen met Matter en Edge AIBieden de nieuwste updates van Matter en de opkomst van Edge AI technici eindelijk de tools om de intelligente, slimme huizen te bouwen die gebruikers zijn beloofd? Differentiële druksensorenVoorspellend onderhoud in HVAC-systemen Security by designTechnische basisprincipes beperken storingen Embedded security is niet langer optioneel CRA en PQC herzien prioriteiten voor embedded securityWaarom zelfs kleine IoT- en industriële bedrijven een upgradeplan nodig hebben embedded world 2026Een interview met Benedikt Weyerer, Executive Director embedded world Praktijkervaring met I3CGebruik van hardware van ST en Microchip Het BLEnky-projectSnelle prototyping voor Bluetooth Low Energy toepassingen Pulsbreedtemodulatievan een eenvoudige aan/uit-thermostaat naar een rimpelloos DC-signaal AudiotronicaOorstrelende elektronica voor zelfbouw Uit het leven gegrepenRead the f...ing manual! ESP32 audio transceiver board (Deel 4)Afstemmen van de kloksignalen en een bekabelde versie 2026: An AI OdysseyDe kater van Vibe-Coding in 2025 Symmetrische DC-belastingStatische of dynamische en symmetrische gelijkstroombelasting Gezichten tellen met MaixCAMEen eenvoudige methode om de omvang van het publiek vast te leggen

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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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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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From Simple Ciphers to Secure Systems Understanding how to apply cryptography on modern microcontrollers is essential for building secure, reliable, and trustworthy systems. This book explains cryptography in the context of embedded hardware, from classical ciphers that illustrate core principles to modern techniques such as AES for practical high-security applications. By combining mathematical theory with real-world microcontroller implementations, readers learn not only how cryptography works, but also how to implement it effectively on systems with limited processing power and memory. The book is intended for students starting out in cryptography, hobbyists securing personal projects, and engineers looking for a structured guide to embedded security. The book covers these key topics in applied cryptography: Classical ciphers on Arduino Uno and Raspberry Pi Pico, with full programs: Spartan Scytale, Hebrew Atbash, Caesar, ROT13, Alberti Disk, Vigenère, Affine, Polybius, Playfair, Beaufort, Ottoman Codebook, and One-Time Pad. Hacking classical ciphers using microcontrollers, with examples. Pseudo-random (PRNG) and true random number generation (TRNG) on microcontrollers. Symmetric-key cryptography with full programs: DES and AES-128/256. Memory and speed constraints of cryptography on microcontrollers. Asymmetric cryptography: public/private keys, digital signatures, key distribution and derivation (KDF), RSA, and SHA-256 implementations. A complete secure communication program using RSA and AES-256. A glossary of commonly used cryptography terms.

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Mit RPi-basierten Tools und Messgeräten Amateurfunkstationen bauen und programmieren Obwohl viele Funkamateure immer noch mit klassischer HF- und Mobilfunkausrüstung arbeiten, ist der Einsatz von Computern und digitalen Techniken inzwischen sehr beliebt. Heutzutage kann jeder für ca. 40 € einen Raspberry Pi-Computer kaufen und fast jede Amateurfunk-Software auf dem 'RPi' ausführen. Die RTL-SDR-Geräte sind bei Funkamateuren sehr beliebt, weil sie sehr preiswert sind und viele Funktionen bieten. Ein Basissystem kann aus einem USB-basierten RTL-SDR-Dongle mit einer geeigneten Antenne, einem RPi-Computer, einem USB-basierten externen Audio-Eingangs-/ Ausgangsadapter und einer auf dem RPi installierten Software bestehen. Mit einer solch einfachen Einrichtung ist es möglich, Signale von etwa 24 MHz bis über 1,7 GHz zu empfangen. Dieses Buch richtet sich an Funkamateure, die lernen wollen, wie man mit dem Raspberry Pi elektronische Projekte baut. Das Buch eignet sich für die gesamte Bandbreite von Anfängern bis hin zu alten Hasen im Amateurfunk. Die schrittweise Installation des Betriebssystems wird mit vielen Details zu den gängigsten Linux-Befehlen beschrieben. Einige Kenntnisse der Programmiersprache Python sind erforderlich, um die im Buch beschriebenen Projekte zu verstehen und zu bearbeiten. Zu den im Buch entwickelten Beispielprojekten gehören eine Stationsuhr, ein Signalgenerator, der Entwurf eines Transistorverstärkers, der Entwurf eines aktiven Filters, ein Morsezeichen-Übungsgerät, ein Frequenzzähler, ein HF-Meter und vieles mehr. Für jedes Projekt werden das Blockdiagramm, der Schaltplan und der vollständige Python-Quellcode angegeben, einschließlich der vollständigen Beschreibung der Projekte. Neben der umfassenden Behandlung von RTL-SDR für Amateurfunk fasst das Buch auch die Installations- und Gebrauchsanweisungen der folgenden Amateurfunkprogramme zusammen, die Sie auf ihrem Raspberry Pi ausführen können: TWCLOCK, Klog, Gpredict, FLDIGI, DIRE WOLF, xcwcp, QSSTV, LinPsk, Ham Clock, CHIRP, xastir und CQRLOG.

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En moins de 100 lignes de code par projet avec les cartes Feather Sense et Clue Express d'Adafruit Le langage de programmation Python est apprécié par les pédagogues parce que sa syntaxe le rend facile à comprendre. Il s'est également imposé chez les informaticiens expérimentés. La société Adafruit a développé une version spéciale de Python pour l'embarquer sur les microcontrôleurs à 32 bits : CircuitPython. Ce livre permettra au lecteur de s'initier à la programmation en CircuitPython sur deux cartes : Feather BlueFruit Sense (également appelée Feather nRF52840 Sense) et CLUE nRF52840 Express. Chacune est animée par le SoC nRF52840 de NORDIC avec une architecture à 32 bits. Pour ce voyage dans le monde de la programmation embarquée, l'auteur sort du chemin classique, à savoir un cours complet sur la programmation orientée objet appliquée à ce langage. Il préfère emmener le lecteur directement sur le terrain avec des projets qui mettent en oeuvre les cartes et différents périphériques. Plus d'une quarantaine d'exemples et de montages permettent de découvrir la richesse de CircuitPython. Toutefois l'auteur s'est imposé une limite pour ne pas décourager les novices : le code de chaque projet ne dépasse jamais la centaine de lignes. Pour ce qui est du matériel, là aussi la simplicité domine : aucun programmateur, un simple PC suffit ; aucun soudage grâce au câblage sur platine d'essai. Les cartes d'extension FeatherWing à enficher sur la Feather nRF52840 Sense permettent de démultiplier ses fonctions : matrice de LED, enregistreur de données, écran à encre électronique, écran OLED, écran TFT, commande de moteurs, audio, relais… Toutes les étapes (assemblage des différents composants, installation des bibliothèques requises, programmation, tests…) sont expliquées en détail. Le code des différents exemples et projets est disponible sur Github. Le résultat de chaque projet est même présenté sur de courtes vidéos disponibles sur YouTube. À la fin de sa lecture, le nouveau Pythonien pourra facilement approfondir les notions abordées et donner vie à ses propres projets grâce aux outils qu'il aura essayés. Ce livre s'adresse aux lycéens et étudiants ainsi qu'à toute la communauté des makers. Chaîne YouTube de l'auteur : YouTube (Michaël Bottin)

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

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This is the second edition of a book aimed at engineers, scientists, and hobbyists who want to interface PCs with hardware projects using graphical user interfaces. Desktop and web-based applications are covered. The programming language used is Python 3, which is one of the most popular languages around: speed of programming being a key feature. The book has been revised and updated with an emphasis on getting the user to produce practical designs with ease – a text editor is all that is required to produce Python programs. Hardware interfacing is achieved using an Arduino Uno as a remote slave. A full description and source code of the communication interface is given in the book. The slave provides digital and analog input and outputs. Multiple Unos can be included in one project with all control code written in Python and running on a PC One project involves a PIC microcontroller with the code provided that can be loaded into the PIC using the Uno. The web applications and server are all implemented in Python, allowing you to access your electronic hardware over the Internet. The Raspberry Pi computer can be used as your web server. An introductory chapter is provided to get you started with using Linux. The book is written for use with Debian or variations including Mint or Ubuntu. All of the programs in the book are freely available, ready to use and experiment with by way of a download from Elektor.

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

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