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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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AI in Practice Dive into the fascinating world of robotics and automation! This Elektor Special shows you how to build your own robots with creativity, a little know-how, and affordable technology. From your first DIY project with Arduino or Raspberry Pi to intelligent systems with AI – this issue makes modern robotics understandable and accessible. Discover practical instructions, inspiring projects, and exciting insights into the maker scene. Learn how experimentation, community, and openness give rise to true innovation – and why robotics is so much more than just a technical hobby. Contents Imagination turns into reality Arduino-controlled Drawing Robot GalaxyRVR Mars Rover Kit for Arduino YDLIDAR X4Pro Lidar xHuskyLens AI Camera DOF Robot Arm with Raspberry Pi Pico Manufacturing Robots with Fischertechnik Pneumatic Industrial Robot Why Do We Keep Building Robot Dogs? Elektor Mini-Wheelie Robot Vehicles and Autonomous Driving

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De Elektor Super Servo Tester kan servo's aansturen en servosignalen meten. Hij kan tot vier servokanalen tegelijkertijd testen. De Super Servo Tester wordt geleverd als bouwpakket. Alle onderdelen die nodig zijn om de Super Servo Tester in elkaar te zetten zijn inbegrepen in de set. Het bouwen van de kit vereist enige basisvaardigheid met solderen. De microcontroller is al geprogrammeerd. De Super Servo Tester beschikt over twee bedrijfsmodi: Control/Manual en Measure/Inputs. In de modus Control/Manual genereert de Super Servo Tester besturingssignalen op zijn uitgangen voor maximaal vier servo's, of voor de flight controller of ESC. De signalen worden ingeregeld door de vier potentiometers. In de modus Measure/Inputs meet de Super Servo Tester de servosignalen die op de ingangen zijn aangesloten. Deze signalen kunnen afkomstig zijn van bijvoorbeeld een ESC, een flight controller, of de ontvanger, of een ander apparaat. De signalen worden ook naar de uitgangen geleid om de servo's of de flight controller of ESC aan te sturen. De resultaten worden op het display weergegeven. Specificaties Operating modi Control/Manual & Measure/Inputs Kanalen 3 Servosignaal ingangen 4 Servosignaal uitgangen 4 Alarm Zoemer & LED Weergave 0,96" OLED (128 x 32 pixels) Ingangsspanning op K5 7 - 12 VDC Ingangsspanning op K1 5 - 7,5 VDC Ingangsstroom 30 mA (9 VDC op K5, en niets aangesloten op K1 en K2) Afmetingen 113 x 66 x 25 mm Gewicht 60 g Inbegrepen Weerstanden (0,25 W) R1, R3 1 k?, 5% R2, R4, R5, R6, R7, R9, R10 10 k?, 5% R8 22 ?, 5% P1, P2, P3, P4 10 k?, lin/B, verticale potentiometer Condensatoren C1 100 ?F 16 V C2 10 ?F 25 V C3, C4, C7 100 nF C5, C6 22 pF Halfgeleiders D1 1N5817 D2 LM385Z-2.5 D3 BZX79-C5V1 IC1 7805 IC2 ATmega328P-PU, geprogrammeerd LED1 LED, 3 mm, rood T1 2N7000 Diversen BUZ1 Piëzo-zoemer met oscillator K1, K2 2-rijige, 12-voudige pinheader, 90° K5 Barrel jack K4 1-rijige, 4-polige pinvoet K3 2-rijige, 6-voudige boxed pinheader S1 Schuifschakelaar DPDT S2 Schuifschakelaar SPDT X1 Kristal, 16 MHz 28-voudige DIP-voet voor IC2 Elektor printplaat OLED-scherm, 0,96", 128 x 32 pixels, 4-pins I²C-interface Links Elektor Magazine Elektor Labs

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Raspberry Pi goes Industry (E-book)

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. PIO Programming on the Raspberry Pi PicoNine Instructions, Many Possibilities Breaking AI Out of the BrowserUsing AI CLIs to Code, Compile, and Validate Embedded Projects The Scrutiny DebuggerDebug, Visualize, and Test Embedded C/C++ Code Sigfox Breakout Board (1)A Self-Built Radio BoB Low-Noise Power Supply (2)Construction, Assembly, and Practical Implementation Simple Signal Generator Using the RP2040Analog and Digital Signals for Around €10 Navigating the Future of Smart Homes with Matter and Edge AIAre Matter’s Latest Updates and the Rise of Edge AI Finally Giving Engineers the Tools to Build the Intelligent, Seamless Smart Homes Users Have Been Promised? Differential Pressure SensorsPredictive Maintenance in HVAC-Systems Security by DesignEngineering Fundamentals Limit Failure Embedded Security Is No Longer Optional CRA and PQC Are Rewriting Embedded Security PrioritiesWhy Even Small IoT and Industrial Firms Need an Upgrade Plan embedded world 2026An Interview With Benedikt Weyerer, Executive Director of embedded world Hands on with I3CUsing Hardware from ST and Microchip The BLEnky ProjectRapid Prototyping of Bluetooth Low Energy Applications Pulse Width ModulationFrom a Simple On/Off Thermostat to a Smoothed DC Analog Signal AudiotronicsEar-Pleasing Electronics for DIY Construction From Life’s ExperienceRead The F...ing Manual! ESP32 Audio Transceiver Board (Part 4)Tuning the Clocks - And a Wired Option 2026: An AI OdysseyThe 2025 Vibe-Coding Hangover Symmetrical DC LoadDC Load, Static or Dynamic, and Symmetrical Counting Faces with MaixCAMAn Easy Way to Capture Audience Sizes

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For Raspberry Pi, ESP32 and nRF52 with Python, Arduino and Zephyr Bluetooth Low Energy (BLE) radio chips are ubiquitous from Raspberry Pi to light bulbs. BLE is an elaborate technology with a comprehensive specification, but the basics are quite accessible. A progressive and systematic approach will lead you far in mastering this wireless communication technique, which is essential for working in low power scenarios. In this book, you’ll learn how to: Discover BLE devices in the neighborhood by listening to their advertisements. Create your own BLE devices advertising data. Connect to BLE devices such as heart rate monitors and proximity reporters. Create secure connections to BLE devices with encryption and authentication. Understand BLE service and profile specifications and implement them. Reverse engineer a BLE device with a proprietary implementation and control it with your own software. Make your BLE devices use as little power as possible. This book shows you the ropes of BLE programming with Python and the Bleak library on a Raspberry Pi or PC, with C++ and NimBLE-Arduino on Espressif’s ESP32 development boards, and with C on one of the development boards supported by the Zephyr real-time operating system, such as Nordic Semiconductor's nRF52 boards. Starting with a very little amount of theory, you’ll develop code right from the beginning. After you’ve completed this book, you’ll know enough to create your own BLE applications.

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Affordable solutions with the ESP8266 and 3D printing If you are looking for a small yet powerful IoT device, you are likely to come across the ESP8266 and compatible products on the market today. One of these, the Wemos/Lolin D1 Mini Pro board strikes a remarkable balance between cost and performance. A small and very affordable prototype board, the D1 Mini Pro stands out with its WiFi functionality and a 16-Mbytes flash memory for easy creation of a flash file system. In addition, there are sufficient input and output pins (only one analog input though) to support PWM, I²C, and One-Wire systems to mention but a few. The book describes the operation, modding, construction, and programming of home appliances including a colorful smart home accessory, a refrigerator/greenhouse controller, an AC powerline monitor, a door lock monitor, and an IKEA Trådfri controller. As a benefit, all firmware developed for these DIY, "IoT-ized" devices can be updated over-the-air (OTA). For most of the designs in the book, a small printed circuit board (PCB) and an enclosure are presented so readers can have a finished and attractive-looking product. Readers having – or with access to! – a 3D printer can "print" the suggested enclosures at home or in a shop. Some of the constructions benefit from a Raspberry Pi configured as a gateway or cms server. This is also described in detail with all the necessary configuring. You don’t need to be an expert but the prerequisites to successful replication of the projects include basic skills with PC software including the ability to surf the Internet. In terms of hardware, you should be comfortable with soldering and generally assembling the PCBs presented in the book. All custom software written for the IoT devices, the PCB layouts, and 3D print files described in the book are available for free downloading.

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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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Raspberry Pi 5 provides two four-lane MIPI connectors, each of which can support either a camera or a display. These connectors use the same 22-way, 0.5 mm-pitch “mini” FPC format as the Compute Module Development Kit, and require adapter cables to connect to the 15-way, 1 mm-pitch “standard” format connectors on current Raspbery Pi camera and display products.These mini-to-standard adapter cables for cameras and displays (note that a camera cable should not be used with a display, and vice versa) are available in 200 mm, 300 mm and 500 mm lengths.

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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. programmation PIO sur le Raspberry Pi PicoNeuf instructions, de multiples possibilités l'IA en ligne de commandeDéveloppement, compilation et validation de projets embarqués depuis le terminal le Scrutiny DebuggerDéboguer, visualiser et tester du code C/C++ embarqué carte breakout Sigfox (1)Développement d’une BoB radio alimentation à faible bruit (2)Construction, assemblage et mise en œuvre pratique générateur de signaux simple basé sur le RP2040Signaux analogiques et numériques à la découverte du futur de la domotique avec Matter et l’IA EdgeLes dernières versions de Matter et l’essor de l’IA en périphérie de réseau (edge) donnent-ils enfin aux ingénieurs les outils nécessaires pour construire les maisons intelligentes et parfaitement intégrées promises aux utilisateurs ? capteurs de pression différentielleLa maintenance prédictive appliquée aux systèmes CVC la sécurité dès la conceptionPrincipes d’ingénierie pour limiter les défaillances la sécurité des systèmes embarqués n’est plus une option la CRA et la PQC redéfinissent les priorités de la sécurité embarquéePourquoi même les petites entreprises IoT et industrielles doivent prévoir une mise à niveau embedded world 2026Entretien avec Benedikt Weyerer, directeur d’embedded world prise en main du bus I3CUtilisation de matériel de ST et Microchip le projet BLEnkyPrototypage rapide d’applications Bluetooth Low Energy modulation de largeur d’impulsionDu thermostat tout ou rien à un signal analogique continu filtré audiotroniqueDes circuits audio agréables à l’écoute, à réaliser soi-même sur le vifLisez donc le manuel ! carte émetteur-récepteur audio ESP32 (4)Réglage des horloges et une option filaire 2026 : une odyssée de l’IAConséquences du vibe coding charge CC symétriqueCharge CC symétrique, statique ou dynamique comptage de visages avec MaixCAMUne méthode simple pour estimer la taille d’un public

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De FNIRSI DLA-serie combineert krachtige USB 3.0-logica-analyse met flexibele, meerkanaals signaalregistratie voor het debuggen en analyseren van digitale circuits en embedded systemen. De serie is verkrijgbaar in twee uitvoeringen: de DLA-16 Plus met 16 digitale kanalen en de DLA-32 Plus met 32 digitale kanalen. Beide modellen bieden samplingfrequenties tot 1 GSa/s, 4 Gbit intern geheugen en ondersteuning voor meer dan 120 protocoldecoders. Dankzij de acquisitiemodi Buffer, Stream en Roll zijn ze geschikt voor zowel snelle signaalanalyse als langdurige monitoring. Kies de DLA-16 Plus voor hogere samplingfrequenties bij gebruik van alle kanalen, of de DLA-32 Plus wanneer u meer kanalen en geavanceerde seriële en parallelle triggering nodig heeft. Kenmerken Verkrijgbaar met 16 of 32 digitale ingangskanalen Bemonsteringssnelheid tot 1 GSa/s DLA-16 Plus: tot 500 MSa/s bij gebruik van alle 16 kanalen DLA-32 Plus: tot 250 MSa/s bij gebruik van alle 32 kanalen 4 Gbit intern geheugen High-speed USB 3.0-interface Acquisitiemodi: Buffer, Stream en Roll Ondersteuning voor meer dan 120 protocoldecoders Geavanceerde triggeropties 4 PWM-uitgangen met een frequentiebereik van 1 Hz tot 20 MHz Data-export naar CSV en BIN Specificaties DLA-16 Plus DLA-32 Plus Digitale kanalen 16 32 Max. Sampling rate 1 GSa/s Sampling rate (1 kanaal) 1 GSa/s Sampling rate (8 kanalen) 1 GSa/s Max. Buffer sampling 16 kanalen @ 500 MSa/s 32 kanalen @ 250 MSa/s Max. Stream sampling 16 kanalen @ 125 MSa/s 32 kanalen @ 50 MSa/s Hardwaregeheugen 4 Gbit Interface USB 3.0 / USB-C Max. USB-overdrachtssnelheid 5 Gbit/s Acquisitiemodi Buffer / Stream / Roll Protocoldecoders 120+ Ondersteuning voor aangepaste protocollen Ja Triggermodi Stijgende flank, dalende flank, hoog, laag, elke flank Geavanceerde trigger Standaard triggering Serieel en parallel Parallelle triggerfasen – Tot 16 PWM-uitgangen 4 PWM-uitgangsspanning 3,3 V PWM-frequentie 1 Hz–20 MHz Gegevensexport CSV, BIN Afmetingen 90 x 81 x 11,5 mm Inbegrepen 1x FNIRSI DLA-16/32 Plus Logic Analyzer 4 Sets van 5 afgeschermde kabels 18x Mini IC-testhaken (uitvoering met uitgebreide configuratie) 1x USB 3.0-datakabel 10x IC-testhaken 1x Transparante opbergdoos voor testhaken 1x Opbergtas 1x Manual Downloads Manual

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Elektor GREEN and GOLD members can download their digital edition here. Not a member yet? Click here. What to expect This Elektor edition guest-edited by Edge Impulse explores the edge AI workflow, from data collection and model training to deployment and optimization: End-to-End Edge AIA hands-on object detection series that walks through the complete machine learning pipeline on embedded hardware. High-Resolution, High-Speed Object Counting (Nvidia Jetson Nano, TensorRT)Pushing inference speed and precision for visual counting applications. PCB Defect Detection with Computer Vision (Raspberry Pi)Smarter manufacturing through embedded vision. Smart Building Ventilation with Sensor FusionAI-powered environmental optimization for energy efficiency. Analog Meter Reading (Arduino Nicla Vision)A TinyML approach to automating analog infrastructure. Smart Appliance Control Using Voice Commands (Nordic Thingy:53)Speech recognition at the edge. Liquid Classification with TinyML (Seeed Wio Terminal + TDS Sensor)Combining IoT sensing and embedded ML for fluid analysis. Surgery Inventory Object DetectionApplying real-time vision to healthcare logistics. Plus, the magazine includes exclusive interviews with: Edge Impulse co-founders Zach Shelby and Jan Jongboom; Qualcomm Technologies VP of product management Manny Singh; and EDGE AI FOUNDATION CEO Pete Bernard. Also included are a Tech the Future essay titled "AI at the Edge: Powering the Next Generation of Devices," an Industry Case Study on GlobalSense, and more. Contents What the Heck Is Edge AI Anyway?Bringing Intelligence to the Device Meet Edge Impulse StudioEasily Build and Deploy Edge AI Models Keyword Spotting with Edge ImpulseCollect, Train, and Deploy Smart Appliance Control Using Voice Commands with the Nordic Thingy:53 Key Terms for Understanding Edge AI and Machine Learning Crash Course: Getting Started with Edge ImpulseLearn to Collect, Train, and Deploy an ML Model with the Arduino Nano 33 BLE Sense A New Chapter for ArduinoFrom Hobby Board to Edge Computing Powerhouse Getting Started with Object Detection on Edge Devices PCB Defect DetectionComputer Vision with Raspberry Pi Scaling AI to the Smallest Devices Optimizing Power Efficiency in Battery-Driven Edge AI Devices AI ToasterWhen Edge AI Meets Breakfast Thundercomm Rubik Pi 3Raspberry Pi Familiarity Meets Edge AI Leadership, Embedded ML, and the Edge Revolution Vision Language Models for the EdgeCascading Models for Better Reliability Get to Know Edge ImpulseQuestions from the Elektor Community Project Update #5: ESP32-Based Energy MeterUsing Edge AI to Recognize Household Loads Motion Recognition with Anomaly DetectionAn End-to-End Tutorial Smart Ventilation System: Fusing Sound and Environmental DataA Dual-MCU Machine Learning Approach for Automated Window and Louver Control Bringing Voice Control to Earbuds and Headsets AI at the Edge: Powering the Next Generation of Devices

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