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

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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39 Experiments with Raspberry Pi and Arduino This book is about Raspberry Pi 3 and Arduino camera projects. The book explains in simple terms and with tested and working example projects, how to configure and use a Raspberry Pi camera and USB based webcam in camera-based projects using a Raspberry Pi. Example projects are given to capture images, create timelapse photography, record video, use the camera and Raspberry Pi in security and surveillance applications, post images to Twitter, record wildlife, stream live video to YouTube, use a night camera, send pictures to smartphones, face and eye detection, colour and shape recognition, number plate recognition, barcode recognition and many more. Installation and use of popular image processing libraries and software including OpenCV, SimpleCV, and OpenALPR are explained in detail using a Raspberry Pi. The book also explains in detail how to use a camera on an Arduino development board to capture images and then save them on a microSD card. All projects given in this book have been fully tested and are working. Program listings for all Raspberry Pi and Arduino projects used in this book are available for download on the Elektor website.

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This collection features the best of Elektor Magazine's articles on embedded systems and artificial intelligence. From hands-on programming guides to innovative AI experiments, these pieces offer valuable insights and practical knowledge for engineers, developers, and enthusiasts exploring the evolving intersection of hardware design, software innovation, and intelligent technology. Contents Programming PICs from the Ground UpAssembler routine to output a sine wave Object-Oriented ProgrammingA Short Primer Using C++ Programming an FPGA Tracking Down Microcontroller Buffer Overflows with 0xDEADBEEF Too Quick to Code and Too Slow to Test? Understanding the Neurons in Neural NetworksEmbedded Neurons MAUI Programming for PC, Tablet, and SmartphoneThe New Framework in Theory and Practice USB Killer DetectorBetter Safe Than Sorry Understanding the Neurons in Neural NetworksArtificial Neurons A Bare-Metal Programming Guide Part 1: For STM32 and Other Controllers Part 2: Accurate Timing, the UART, and Debugging Part 3: CMSIS Headers, Automatic Testing, and a Web Server Introduction to TinyMLBig Is Not Always Better Microprocessors for Embedded SystemsPeculiar Parts, the Series FPGAs for BeginnersThe Path From MCU to FPGA Programming AI in Electronics DevelopmentAn Update After Only One Year AI in the Electronics LabGoogle Bard and Flux Copilot Put to the Test ESP32 and ChatGPTOn the Way to a Self-Programming System… Audio DSP FX Processor Board Part 1: Features and Design Part 2: Creating Applications Rust + EmbeddedA Development Power Duo A Smart Object CounterImage Recognition Made Easy with Edge Impulse Universal Garden LoggerA Step Towards AI Gardening A VHDL ClockMade with ChatGPT TensorFlow Lite on Small MicrocontrollersA (Very) Beginner’s Point of View Mosquito DetectionUsing Open Datasets and Arduino Nicla Vision Artificial Intelligence Timeline Intro to AI AlgorithmsPrompt: Which Algorithms Implement Each AI Tool? Bringing AI to the Edgewith ESP32-P4 The Growing Role of Edge AIA Trend Shaping the Future

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

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AI Projects for the Raspberry Pi with the AI HAT+ Edge AI is transforming everyday devices by putting intelligence where it matters most: directly inside the hardware. With on-device inference, a camera can recognize a visitor instantly, a phone can translate speech without streaming audio to the cloud, and a wearable can detect anomalies in real time—fast, private, and reliable even when the network disappears. This book is your practical guide to building exactly those kinds of systems with the Raspberry Pi AI HAT+ and the Hailo-8L accelerator. You’ll start with clear foundations: core AI and machine-learning concepts, how neural networks work, and what truly distinguishes Edge AI from cloud AI—plus an honest look at ethical considerations and future impacts. Then it’s straight to hands-on physical computing. Step by step, you’ll set up Raspberry Pi OS, power and cooling, and develop in Python using the Thonny IDE. You’ll learn GPIO basics with lights and servos, mount the AI HAT+ hardware, install and verify the Hailo software stack, and connect the right camera—official modules or USB webcams, even multiple cameras. From your first pipeline to real projects, you’ll run person detection, pose estimation, segmentation, and depth estimation, then level up with YOLO object detection: smart alerts, guest counters, and custom extensions. You’ll even connect vision to motion by combining gesture recognition with servo-driven mechanisms, including a robotic arm. With troubleshooting tips, hardware essentials, and a practical Python refresher, this book turns Edge AI from buzzword into buildable reality.

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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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A Beginner's Guide to AI and Edge Computing Artificial Intelligence (AI) is now part of our daily lives. With companies developing low-cost AI-powered hardware into their products, it is now becoming a reality to purchase AI accelerator hardware at comparatively very low costs. One such hardware accelerator is the Hailo module which is fully compatible with the Raspberry Pi 5. The Raspberry Pi AI Kit is a cleverly designed hardware as it bundles an M.2-based Hailo-8L accelerator with the Raspberry Pi M.2 HAT+ to offer high speed inferencing on the Raspberry Pi 5. Using the Raspberry Pi AI Kit, you can build complex AI-based vision applications, running in real-time, such as object detection, pose estimation, instance segmentation, home automation, security, robotics, and many more neural network-based applications. This book is an introduction to the Raspberry Pi AI Kit, and it is aimed to provide some help to readers who are new to the kit and wanting to run some simple AI-based visual models on their Raspberry Pi 5 computers. The book is not meant to cover the detailed process of model creation and compilation, which is done on an Ubuntu computer with massive disk space and 32 GB memory. Examples of pre-trained and custom object detection are given in the book. Two fully tested and working projects are given in the book. The first project explains how a person can be detected and how an LED can be activated after the detection, and how the detection can be acknowledged by pressing an external button. The second project illustrates how a person can be detected, and how this information can be passed to a smart phone over a Wi-Fi link, as well as how the detection can be acknowledged by sending a message from the smartphone to your Raspberry Pi 5.

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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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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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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 Air 1x Unitree Go2 Battery (8000 mAh) Downloads Documentation iOS/Android apps GitHub

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