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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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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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With the availability of free and open source C/C++ compilers today, you might wonder why someone would be interested in assembler language. What is so compelling about the RISC-V Instruction Set Architecture (ISA)? How does RISC-V differ from existing architectures? And most importantly, how do we gain experience with the RISC-V without a major investment? Is there affordable hardware available? The availability of the Espressif ESP32-C3 chip provides a way to get hands-on experience with RISC-V. The open sourced QEMU emulator adds a 64-bit experience in RISC-V under Linux. These are just two ways for the student and enthusiast alike to explore RISC-V in this book. The projects in this book are boiled down to the barest essentials to keep the assembly language concepts clear and simple. In this manner you will have “aha!” moments rather than puzzling about something difficult. The focus in this book is about learning how to write RISC-V assembly language code without getting bogged down. As you work your way through this tutorial, you’ll build up small demonstration programs to be run and tested. Often the result is some simple printed messages to prove a concept. Once you’ve mastered these basic concepts, you will be well equipped to apply assembly language in larger projects.

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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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There are many so-called 'Arduino compatible' platforms on the market. The ESP8266 – in the form of the WeMos D1 Mini Pro – is one that really stands out. This device includes WiFi Internet access and the option of a flash file system using up to 16 MB of external flash memory. Furthermore, there are ample in/output pins (though only one analogue input), PWM, I²C, and one-wire. Needless to say, you are easily able to construct many small IoT devices! This book contains the following builds: A colourful smart home accessory refrigerator controller 230 V power monitor door lock monitor and some further spin-off devices. All builds are documented together with relevant background information for further study. For your convenience, there is a small PCB for most of the designs; you can also use a perf board. You don’t need to be an expert but the minimum recommended essentials include basic experience with a PC, software, and hardware, including the ability to surf the Internet and assemble PCBs. And of course: A handle was kept on development costs. All custom software for the IoT devices and PCB layouts are available for free download from at Elektor.com.

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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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In 35 Projects with the Raspberry Pi and Arduino The Internet of Things (IoT) is a trend with a strong technological impulse. At home, we want to do everything on our tablets, from browsing Facebook to watching TV, from operating lights to keeping an eye on the temperature. In 35 fun projects, this book will show you how to build your own Internet of Things system. We'll cover the hardware (primarily the Raspberry Pi and Arduino) and the software that makes control via Internet possible. We employ Wi-Fi and radio links so no requirement any longer to install cabling crisscross through your home. Assuming the projects in the book are finished, you have a complete Internet of Things system that allows you to control and view of everything in your home. For example, if there's something in the mail box or the car is securely in the garage. Also, you can switch on the lights and the alarm from your couch. The crisp explanations allow the projects to be customized with ease, for example, to turn on your coffee machine or TV remotely. The index gives easy access to creative projects that can serve as an example, enabling you to do all the connecting to the IoT independently. All project software can be downloaded free of charge from the Elektor website. In this unique book, Raspberry Pi, Arduino and HTML webpages with stylesheets and JavaScript come together in clearly-described, easy-to-build projects. This special book is an essential part of your collection!

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Ready-to-use devices and self-built Arduino nodes in the 'The Things Network' LoRaWAN has developed excellently as a communication solution in the IoT. The Things Network (TTN) has contributed to this. The Things Network was upgraded to The Things Stack Community Edition (TTS (CE)). The TTN V2 clusters were closed towards the end of 2021. This book shows you the necessary steps to operate LoRaWAN nodes using TTS (CE) and maybe extend the network of gateways with an own gateway. Meanwhile, there are even LoRaWAN gateways suitable for mobile use with which you can connect to the TTN server via your cell phone. The author presents several commercial LoRaWAN nodes and new, low-cost and battery-powered hardware for building autonomous LoRaWAN nodes. Registering LoRaWAN nodes and gateways in the TTS (CE), providing the collected data via MQTT and visualization via Node-RED, Cayenne, Thingspeak, and Datacake enable complex IoT projects and completely new applications at very low cost. This book will enable you to provide and visualize data collected with battery-powered sensors (LoRaWAN nodes) wirelessly on the Internet. You will learn the basics for smart city and IoT applications that enable, for example, the measurement of air quality, water levels, snow depths, the determination of free parking spaces (smart parking), and the intelligent control of street lighting (smart lighting), among others.

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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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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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This hands-on bundle lets you build real Edge AI applications with the Raspberry Pi Raspberry Pi AI HAT+ (13 TOPS) The Raspberry Pi AI HAT+ (13 TOPS) is an expansion board designed for the Raspberry Pi 5, featuring an integrated Hailo AI accelerator. This add-on offers a cost-effective, efficient, and accessible approach to incorporating high-performance AI capabilities, with applications spanning process control, security, home automation, and robotics. The AI HAT+ connects via the Raspberry Pi 5’s PCIe Gen3 interface. When the Raspberry Pi 5 is running a current version of the Raspberry Pi OS, it automatically detects the onboard Hailo accelerator, making the neural processing unit (NPU) available for AI tasks. Additionally, the rpicam-apps camera applications included in Raspberry Pi OS seamlessly support the AI module, automatically using the NPU for compatible post-processing functions. Raspberry Pi Camera Module 3 Raspberry Pi Camera Module 3 is a compact camera from Raspberry Pi. It offers an IMX708 12-megapixel sensor with HDR, and features phase detection autofocus. Camera Module 3 is available in standard and wide-angle variants, both of which are available with or without an infrared cut filter. Camera Module 3 can be used to take full HD video as well as stills photographs, and features an HDR mode up to 3 megapixels. Its operation is fully supported by the libcamera library, including Camera Module 3’s rapid autofocus feature: this makes it easy for beginners to use, while offering plenty for advanced users. Camera Module 3 is compatible with all Raspberry Pi computers. Book: Edge AI Made Practical – 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. This bundle contains: Book: Edge AI Made Practical Raspberry Pi AI HAT+ (13 TOPS) Raspberry Pi Camera Module 3 Active Cooler for Raspberry Pi 5 FPC Display Cable for Raspberry Pi 5 (300 mm) Elektor Component Kit 40-pin GPIO Header Traffic Light Module LED red 5 V with built-in resistor LED yellow 5 V with built-in resistor LED green 5 V with built-in resistor LED blue 5 V with built-in resistor Breadboard (400 Tie-points) 10 Dupont wires male-female DHT22 sensor module Servo motor Required Raspberry Pi 5

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