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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The Raspberry Pi 5A Huge Improvement From Its Predecessor
AI in the Electronics LabGoogle Bard and Flux Copilot Put to the Test
Arduino Nano Waveform GeneratorNano + Code = Function Generator
Solar-Powered Christmas GarlandAn Eco-Friendly Solution for Garnishing Your Balcony
USB Killer DetectorBetter Safe Than Sorry
A Simple CNCed EnclosureWith Autodesk Fusion 360 for Personal Use
Low-Volume Board ProductionWith and without Assembly
IoT Simulation Simplified with WokwiDeveloper Uri Shaked on Design, Software, and More
A Bare-Metal Programming Guide (Part 3)CMSIS Headers, Automatic Testing, and a Web Server
LoRa, a Swiss Army Knife (2)The Hardware and Software
MEMS Microphone Design and Construction
Tools to Try Before You SolderSimulation and 3D Modeling Tools That Can Be Used for Free
New Tools From Microchip!PICkit 5 and MPLAB ICD 5 Available Now!
Rapid Prototyping of Flexible, Stretchable ElectronicsHow the Voltera NOVA Speeds Up Innovation in Wearable Electronic Systems
Galvanic IsolationUsing Phototransistor Optocouplers Successfully
The Complex Solution or the Anybus Solution?Embedded Industrial Ethernet in 2 Days Rather Than Many Months
Your Essential DFM ChecklistHow to Start Designing for Manufacture
3D Printing FilamentsTypes, Features and Use in Prototyping
Specialists for Effective Signal Analysis from ELF to EHF BandAaronia’s latest real-time SPECTRAN® V6 series spectrum analyzers
Challenges of DFM Analysis for Flex and Rigid-Flex Design
Setting Up an SMT Line
The Right Combination for a Reliable Assembly
Revolutionizing IndustriesThe Rise of Autonomous Mobile Robots (AMRs)
Evolved for More ChallengesRohde & Schwarz Adds Eight-Channel R&S MXO 5 to Next-Generation Oscilloscopes
Starting Out in Electronics……Amplifying Differences
Mini Reflow PlateFor Assembling or Repairing Small SMD Circuits
Don’t Start with a Prototype – Start with a Pretotype!Check That a Market Exists for Your Product Before Warming Your Soldering Iron
2023: An AI OdysseyGetting Help Designing a Physical Project
Brussels Is InnovatingSupport for Deep Tech
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tableau de bord OBD2Des cadrans anciens aux données en temps réel
OBD2 : ajoutez un compte-tours et un indicateur de changement de vitesse à votre voitureRétro, mais extrêmement utile
capteurs de vision et LiDAR pour la robotique
Sensor+Test 2025 et PCIM 2025
mesures sans contact du champ électrique (1)Membrane vibrante pour mesurer des tensions continues ou des champs électriques statiques
détecteur de courrier sans filCapteurs optiques, radars… quelques options à explorer
Elektor Mini-WheelieUn robot auto-équilibré
cellules solairesDrôles de composants, la série
premiers pas avec un capteur radar moderneUn capteur précis qui ne passe pas inaperçu
sur le vifUsine de papier
CybersécuritéDes temps difficiles pour les hackers
Infographie : IdO et capteurs
le Bluetooth 6.0 pour des applications de télémétrie amélioréesCette nouvelle version offre des fonctions de localisation améliorées
découvrez la communication sans fil avec BeagleY-AI
Projet 2.0Corrections, mises à jour et courrier des lecteurs
démarrer en électronique……Conclusion sur les ampli-op
un puissant assistant de codage de l'IAAccélérez votre développement avec Continue et Visual Studio Code
contrôleur de charge solaire avec MPPT (2)Le circuit
détecteur d'obstacles à ultrasonsUn projet simple pour aider les malvoyants
une odyssée de l'IABilan du premier semestre
synthétiseur MIDI autonome Raspberry Pi (3)plus intelligent avec une interface utilisateur
Meshtastic : un projet de démoUn réseau intelligent de noeuds LoRa
générateur analogique de fréquences audioGénérateur de signaux sinusoïdaux de haute qualité à fréquence réglable
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The RISC-V Open-Source Processor Architecture16 Boards and MCUs You Should Know
An FPGA-Based Audio Player with Equalizer (1)Mixing Digital Audio with an Arduino MKR Vidor 4000
Laser Head for Pico-Based Sand ClockDrawing with Light
Enter the STM32 Edge AI Contest
A Multi-Sensor Environmental Monitoring System for PlantsWireless Measurement of Water Supply and Light Conditions
Maixduino AI-Powered Automatic DoormanFace Detection with a Camera
Embedded Electronics 2024AI Is Set to Redefine the Industry
Charge-Based In-Memory Compute at EnCharge AI
AI Inferencing at 10 Times Lower Power and 20 Fold Lower Cost
Click Board Helps Develop and Train ML Models for Vibration Analysis
The Elektor Mini-WheelieA Self-Balancing Robot Kit
MCU, I See YouMCUViewer Open-Source Multiplatform Debugging Tool
USB 2.0 IsolatorElectrically Isolated Connections for USB Devices
Intervention Before DamagePredictive Maintenance in Practice
SPoE – Electromagnetic CompatibilitySingle-Pair with Power-Over-Ethernet Through the Eyes of EMC
Color TV: A Wonder of Its TimeCreating a New World
ECG Graph MonitoringAn Implementation with Hexabitz Modules and an STM32CubeMonitor
The Battle for AI at the Edge
HaLow Hits Record 16-km Wi-Fi Distance at 900 MHz
First CHERI RISC-V Embedded Chip and Early Access Programme
Third-Generation Wildfire Detection Uses Satellite Links
From Life’s ExperienceChoice Overload
Starting Out in Electronics……Continues Filtering and Controls Tone
Quasi-Analog ClockworkA Remake of an Elektor Classic
A Modular Approach to Sensor TestingThe ESP32-S3-Based Sensor Evaluation Board
2025: An AI OdysseyThe Rise of Foundation Models and Their Role in Democratizing AI
Raspberry Pi Standalone MIDI Synthesizer (1)Preparing a Platform for Some Edge AI Experiments
Err-lectronicsCorrections, Updates, and Readers’ Letters
Universal AI RISC-V Processor Does It All — CPU, GPU, DSP, FPGA
CEO Interview: Ventiva’s Thin and Cool Tech
Dual-Core Programming with a Raspberry Pi PicoVenture Into the World of Parallel Programming
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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
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.
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
Elektor GREEN and GOLD members can download their digital edition here.
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Relio v1.0 - Presence Detection and Remote ControlA Matter-Enabled Smart Controller for AC Appliances
Designing Better PCBsA Practical Guide for Professionals and Makers
KiCad 9Top New and Updated Features
Precision Picoammeter (1)With Curve Tracer Functionality Down to the pA range!
Christmas Star 2025A Star Is Soldered
100 mV Continuity Tester
Who’s Pushing the Boundaries of European Electronics?Companies to Watch
productronica 2025: What’s New in Electronics Development and Production
Automation to Tackle Reshoring Manufacturing, Tariffs and Labour Shortages
Beyond Future ProofCircularity in Electronics
Passive ComponentsLow-Loss Inductors Enabling High-Efficiency DC/DC Converters
How Desktop Manufacturing Machines Are Democratizing PCB Production
Starting Out in Electronics...Needs Power
UHD Displays Driven with EaseYour Guide to Easily Put Various TFT-LCDs Into Operation Quickly
Soldering in 2025Practical Soldering Tips Straight from the Workbench
SimulIDEAn All-in-One Tool for Circuit Prototyping
2025: An AI OdysseyFrom Autocomplete to Colleague
Wordy Christmas TreeA Festive Electronics Project with a Linguistic Twist
Err-lectronicsCorrections, Updates, and Readers’ Letters
Analog Pipeline DistortionA Cool Audio Effect For Guitars and Other Instruments
ESP32 Audio Transceiver Board (Part 3)Stereo Transmission and Dual Radio
KENNISMAKING MET NEURONEN IN NEURALE NETWERKEN (DEEL 1)Kunstmatige Neuronen
EMC PRE-COMPLIANCE TEST VOOR UW DC-GEVOED PROJECT (DEEL 1)Dubbele DC-LISN
ELEKTRONISCHE BELASTING VOOR DC EN ACTot 400 V en 10 A (piek)
ALLE BEGIN......neemt het op tegen de spoel!
BEELDVERWERKING MET DE NVIDIA JETSON NANO (DEEL 1)De Hardware en Software
EEN GEDETAILLEERD ONDERZOEK NAAR NETTRANSFORMATORENIn- en uitschakelgedrag
YES WE CAN MET PICAN 3Een CAN Bus HAT voor de Raspberry Pi 4
ZONNEPANELEN OP JE BALKONZelfbouw balkoncentrale = snel terugverdiend!
BEELDVERWERKING EN VIDEO-STREAMING MET EEN RASPBERRY PI 4De Raspberry Pi High-Quality Camera in de praktijk
DISPLAYS GEBRUIKEN IN RASPBERRY PI-PROJECTENEen hoofdstuk als voorbeeld: Organische LED-displays (OLED)
KENNISMAKING MET DE PARALLAX PROPELLER 2 (DEEL 4):Tekens Versturen
ELEKTOR @ 60Een terugblik op voorgaande septembers
OOST WEST LAB BESTop het Friese platteland, waar de buizen bloeien...
HYBRIDENVreemde onderdelen, de serie
EEN KOMPASROOS MET DE GY-271Of waarom we in een acht bewegen om een sensor te kalibreren
HOE GROOT IS UW VOETAFDRUK?Bereken de ecologische voetafdruk van uw elektronica
CONNECTED THERMOSTAAT MET ESP32Houd uw wijn op de juiste temperatuur!
MAGNETISCHE LEVITATIE OP DE DIGITALE MANIERESP32 Pico vervangt de Analoge Comparator
ULTIMATE ARDUINO UNO HARDWARE MANUALEen hoofdstuk als voorbeeld: Main Microcontroller Bootloader
MICROPYTHON VOOR DE ESP32 C.S. (DEEL 2)Eenvoudig Matrix Displays besturen
MADMACHINE SWIFTIO BOARDModerne taal ontmoet moderne Hardware
UIT HET LEVEN GEGREPENKnipperlichtrelatie
HEXADOKUThe Original Elektorized Sudoku
The tinySA Ultra+ ZS-407 is a compact, handheld spectrum analyzer and signal generator. Covering 100 kHz to 7.3 GHz in Ultra mode, it lets you visualize and analyze RF signals from HF right through many modern wireless bands – and can even spot signals up to ~12 GHz thanks to harmonic tracking.
The intuitive 4-inch resistive touchscreen and rechargeable battery make it great for fieldwork, while features like a built-in signal generator, switchable bandpass filters, step attenuator, USB-PC control and auto-calibration add serious versatility.
Caractéristiques
Screen size: 4 inch (480 x 320)
Spectrum Analyzer for 0.1-900 MHz or, with Ultra mode enabled up to 7.3 GHz, level calibrated up to 7.3 GHz. Can observe signals up to 12 GHz
Signal Generator with sine wave output between 0.1-900 MHz or square wave up to 6.3 GHz or RF test signal output up to 7.3 GHz when not used as Spectrum Analyzer.
Switchable resolution bandpass filters from 200 Hz to 850 kHz
Built-in 20 dB optional LNA
Color display showing max 450 points providing gapless covering up to the full frequency range.
MicroSD card slot for storing measurements, settings and screen captures.
Spécifications (Analyseur de spectre)
Input frequency range from 100 kHz to 900 MHz in normal mode and up to 7.3 GHz with ULTRA mode enabled
Input impedance 50 ohm when input attenuation set to 10 dB or more.
Selectable manual and automatic input attenuation between 0 dB and 31 dB in 1 dB steps when LNA not active
Maximum +/-5V DC input
Absolute maximum input level of +6 dBm with 0 dB internal attenuation
Absolute maximum short term peak input power of +20 dBm with 30 dB internal attenuation
Suggested maximum input power of +0 dBm with internal attenuation in automatic mode
For best measurements keep input power below -25 dBm
Input Intercept Point of third order modulation products (IIP3) of +15 dBm with 0 dB internal attenuation
1 dB compression point at -1 dBm with 0 dB internal attenuation
Power detector resolution of 0.5 dB and linearity versus frequency of ±2 dB below 5.3 GHz, ±5dB between 5.3 GHz and 6 GHz
Minimum burst length for correct level measurement at 850 kHz RBW in zero span mode of 50 microseconds
Absolute power level accuracy after power level calibration of ±2 dB
Built-in optional 20 dB LNA with Noise Figure of 5 dB up to 6 GHz
Lowest discernible signal without LNA at 30 MHz using a resolution bandwidth of 30 kHz of -102 dBm
Lowest discernible signal with LNA at 30 MHz using a resolution bandwidth of 200 Hz of -145 dBm
Frequency accuracy equal to the selected resolution bandwidth
Phase noise at 30 MHz of -108 dB/Hz at 100 kHz offset and -115 dB/Hz at 1MHz offset
Spur free dynamic range when using a 30 kHz resolution bandwidth of 70 dB
Resolution filters with a width of 0.2, 1, 3, 10, 30, 100, 300, 600 and 850 kHz
On screen resolution of 51, 101, 145, 290 or 450 measurement points.
Scanning speed of over 1000 points/second using largest resolution filters.
Automatic optimization of actual scanning points to ensure coverage of the whole scan range regardless of the chosen resolution bandwidth
Spur suppression option for assessing if certain signals are internally generated or actually present in the input signal
Headphone output for listening to the demodulated audio (AM only). Stereo connector with or without microphone, high impedance is louder, short protected
Spécifications (Générateur de signaux)
Sine wave output with harmonics below -40 dB of fundamental from 100 kHz to 900 MHz
Output level selectable in 1 dB steps between -115 dBm and -19 dBm
Above 800 MHz choice of two output modes:
Cleanest signal mode: square wave, up to 6 GHz with coarse frequency steps and less accurate output level
Highest accuracy mode: reduced harmonics with possibly strong spurs up to 7.3 GHz with frequency resolution equal to below 800 MHz and fine output level steps
Level accuracy ±2 dB up to 800 MHz between -72 dBm and -19 dBm, less accuracy below -72 dBm, even less accuracy below -110 dBm
Output frequency resolution 57.2 Hz
Optional AM or FM modulation frequencies between 50 Hz and 5 kHz (AM) or 1 kHz (FM) or sweep over selectable frequency span
AM modulation depth between 10% and 100%
FM deviation between 1 kHz and 300 kHz
Optional output level sweep over maximum the entire output level range
Inclus
1x tinySA Ultra+ ZS407 Spectrum Analyzer
2x SMA connection cables
1x Barrel connector
1x Antenna with SMA connector
1x USB-C cable
1x microSD card (32 GB)
Téléchargements
Wiki
Elektor GREEN en GOLD leden kunnen deze uitgave hier downloaden.
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STM32 Wireless Innovation Design Contest: de winnaars
In-circuit LC-meteroverwegingen bij een prototype
AmpVolt: een modulaire DC-vermogensmeter (deel 1)meet gelijkstroom en energieverbruik tot 50 V en 5 A
embedded world 2024
Elektronische apparatuur reparerentools, technieken en tips
Alle begin... - NL TRANSLATION...gaat verder met de opamp-theorie
Eenvoudige DDS-signaalgeneratordirecte digitale synthese in zijn puurste vorm
Sparkplug bekekenspecificatie voor MQTT-data
De CRTCvreemde onderdelen
Radargestuurde verlichtingautomatische trapverlichting met personendetectie
Digitale waterpas en actieve stroboscoop voor draaitafelsregel je platenspeler perfect af met dit alles-in-één tool
Onderzoek naar de uitdagingen en commerciële waarde van open source-elektronica (2)
Ronde M12-connector met A-coderingvoorkeursoplossing voor industriële toepassingen
Het Arduino-Inside Measurement Labeen 8-in-1 test- en meetinstrument voor de elektronica-werkbank
Frequentie-, fase- en impedantieanalyse met een geluidskaartvoor frequenties van 100 Hz tot 90 kHz
Zuurgraad meten met de Arduino UNO R4controleer de waterkwaliteit
Uit het leven gegrepenpangpongbilletjes-lanceermachine
FNIRSI 1014D digitale geheugenoscilloscoopgoede prestaties voor weinig geld
2024: een AI-odysseeobjectdetectie aan de praat krijgen
10MHz-referentiegeneratorzeer nauwkeurig, met verdeler en galvanische isolatie
Project-update #2: ESP32-gebaseerde energiemeterenkele verbeteringen
Project 2.0correcties, updates en brieven van lezers
Een vraaggesprek met Eben Upton, CEO van Raspberry Pide Raspberry Pi 5 – en daarna
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.