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The Milk-V Duo 256M is an ultra-compact embedded development platform based on the SG2002 chip. It can run Linux and RTOS, providing a reliable, low-cost, and high-performance platform for professionals, industrial ODMs, AIoT enthusiasts, DIY hobbyists, and creators. This board is an upgraded version of Duo with a memory boost to 256M, catering to applications demanding larger memory capacities. The SG2002 elevates computational power to 1.0 TOPS @ INT8. It enables seamless switching between RISC-V/ARM architectures and supports simultaneous operation of dual systems. Additionally, it includes an array of rich GPIO interfaces such as SPI, UART, suitable for a wide range of hardware development in edge intelligent monitoring, including IP cameras, smart peephole locks, visual doorbells, and more. SG2002 is a high-performance, low-power chip designed for various product fields such as edge intelligent surveillance IP cameras, smart door locks, visual doorbells, and home intelligence. It integrates H.264 video compression and decoding, H.265 video compression encoding, and ISP capabilities. It supports multiple image enhancement and correction algorithms such as HDR wide dynamic range, 3D noise reduction, defogging, and lens distortion correction, providing customers with professional-grade video image quality. The chip also incorporates a self-developed TPU, delivering 1.0 TOPS of computing power under 8-bit integer operations. The specially designed TPU scheduling engine efficiently provides high-bandwidth data flow for all tensor processing unit cores. Additionally, it offers users a powerful deep learning model compiler and software SDK development kit. Leading deep learning frameworks like Caffe and Tensorflow can be easily ported to its platform. Furthermore, it includes security boot, secure updates, and encryption, providing a series of security solutions from development, mass production, to product applications. The chip integrates an 8-bit MCU subsystem, replacing the typical external MCU to achieve cost-saving and power efficiency goals. Specifications SoC SG2002 RISC-V CPU C906 @ 1 Ghz + C906 @ 700 MHz Arm CPU 1x Cortex-A53 @ 1 GHz MCU 8051 @ 6 KB SRAM Memory 256 MB SIP DRAM TPU 1.0 TOPS @ INT8 Storage 1x microSD connector or 1x SD NAND on board USB 1x USB-C for power and data, USB Pads available CSI 1x 16P FPC connector (MIPI CSI 2-lane) Sensor Support 5 M @ 30 fps Ethernet 100 Mbps Ethernet with PHY Audio Via GPIO Pads GPIO Up to 26x GPIO Pads Power 5 V/1 A OS Support Linux, RTOS Dimensions 21 x 51 mm Downloads Documentation GitHub

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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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The unPhone is an open-source IoT development platform powered by the ESP32S3 microcontroller. It features integrated LoRa, Wi-Fi, and Bluetooth connectivity, a touchscreen, and a LiPo battery, offering a robust and versatile solution for IoT development. Its compatibility with Adafruit's FeatherWing standard enables easy expansion, making it an ideal choice for educators, makers, and developers seeking a flexible and user-friendly platform. Features ESP32S3 microcontroller (with 8 MB flash and 8 MB PSRAM) LoRaWAN licence-free radio communication (plus the ESP32's excellent wifi and bluetooth support) 3.5" (320 x 480) LCD capacitive touchscreen for easy debugging and UI creation IR LEDs for surreptitiously switching the cafe TV off 1200 mAh LiPo battery with USB-C charging Vibration motor for notifications Compass/Accelorometer A robust case SD card slot Power and reset buttons Programmable in C++ or CircuitPython Expander board that supports two Featherwing sockets and a prototyping area Open source firmware compatible with the Arduino IDE, PlatformIO and Espressif's IDF development framework Included unPhone (assembled) Expander board FPC cable (to link the expander board to unPhone) Self adhesive mounts for the expander board Code Examples C++ library Kick the tyres on everything in the box The main LVGL demo CircuitPython Support forum Textbook (especially chapter 11)

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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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The MKR IoT Carrier comes equipped with 5 RGB LEDs, 5 capacitive touch buttons, a colored display, IMU and a variety of quality sensors. It also features a battery holder for a 18650 Li-Ion battery, SD card holder and Grove connectors. Data Capture: Map the environment around the carrier using the integrated temperature, humidity, and pressure sensors and collect data about movement using the 6 axis IMU and light, gesture, and proximity sensors. Easily add more external sensors to capture more data from more sources via the on-board Grove connectors (x3). Data Storage: Capture and store all the data locally on an SD card, or connect to the Arduino IoT Cloud for real-time data capture, storage, and visualization. Data Visualisation: Locally view real-time sensor readings on the built-in OLED Color Display and create visual or sound prompts using the embedded LEDs and buzzer. Total Control: Directly control small-voltage electronic appliances using the onboard relays and the five tactile buttons, with the integrated display providing a handy on-device interface for immediate control.

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The AVR-IoT WA development board combines a powerful ATmega4808 AVR MCU, an ATECC608A CryptoAuthentication secure element IC and the fully certified ATWINC1510 Wi-Fi network controller – which provides the most simple and effective way to connect your embedded application to Amazon Web Services (AWS). The board also includes an on-board debugger, and requires no external hardware to program and debug the MCU. Out of the box, the MCU comes preloaded with a firmware image that enables you to quickly connect and send data to the AWS platform using the on-board temperature and light sensors. Once you are ready to build your own custom design, you can easily generate code using the free software libraries in Atmel START or MPLAB Code Configurator (MCC). The AVR-IoT WA board is supported by two award-winning Integrated Development Environments (IDEs) – Atmel Studio and Microchip MPLAB X IDE – giving you the freedom to innovate with your environment of choice. Features ATmega4808 microcontroller Four user LED’s Two mechanical buttons mikroBUS header footprint TEMT6000 Light sensor MCP9808 Temperature sensor ATECC608A CryptoAuthentication™ device WINC1510 WiFi Module On-board Debugger Auto-ID for board identification in Atmel Studio and Microchip MPLAB X One green board power and status LED Programming and debugging Virtual COM port (CDC) Two DGI GPIO lines USB and battery powered Integrated Li-Ion/LiPo battery charger

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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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The Arduino Pro Portenta Cat. M1/NB IoT GNSS Shield allows you to enhance the connectivity features of your Portenta H7 applications. The shield leverages a Cinterion TX62 wireless module by Thales, designed for highly efficient, low-power IoT applications to deliver optimized bandwidth and performance. The Portenta Cat. M1/NB IoT GNSS Shield combines with the strong edge computing power of the Portenta H7 to enable the development of asset tracking and remote monitoring applications in industrial settings, as well as in agriculture, public utilities and smart cities. The shield offers cellular connectivity to both Cat. M1 and NB-IoT networks with the option to use eSIM technology. Easily track your valuables – across the city or worldwide – with your choice of GPS, GLONASS, Galileo or BeiDou. Features Change connectivity capabilities without changing the board Add NB-IoT, CAT. M1 and positioning to any Portenta product Possibility to create a small multiprotocol router (WiFi - BT + NB-IoT/CAT. M1) Greatly reduce communication bandwidth requirements in IoT applications Low-power module Compatible also with MKR boards Remote Monitoring Industrial and agricultural companies can leverage the Portenta Cat. M1/NB IoT GNSS Shield to remotely monitor gas detectors, optical sensors, machinery alarm systems, biological bug traps and more. Technology providers providing smart city solutions can compound the power and reliability of the Portenta H7 with the Portenta Cat. M1/NB IoT GNSS Shield, to connect data and automate actions for a truly optimized use of resources and enhanced user experience. Asset Monitoring Add monitoring capabilities to any asset by combining the performance and edge computing features of the Portenta family boards. The Portenta Cat. M1/NB IoT GNSS Shield is ideal to monitor valuable goods and also for monitoring industrial machinery and equipment. Specifications Connectivity Cinterion TX62 wireless module; NB-IoT - LTE CAT.M1; 3GPP Rel.14 Compliant Protocol LTE Cat. M1/NB1/NB2; UMTS BANDS: 1 / 2 / 3 / 4 / 5 / 8 / 12(17) / 13 / 18 / 19 / 20 / 25 / 26 / 27 / 28 / 66 / 71 / 85; LTE Cat.M1 DL: max. 300 kbps, UL: max. 1.1 Mbps; LTE Cat.NB1 DL: max. 27 kbps, UL: max. 63 kbps; LTE Cat.NB2 DL: max. 124 kbps, UL: max. 158 kbps Short messaging service (SMS) Point-to-point mobile terminated (MT) and mobile originated (MO) Text Mode; Protocol Data Unit (PDU) Mode Localization support GNSS capability (GPS/BeiDou/Galileo/GLONASS) Other Embedded IPv4 and IPv6 TCP/IP stack access; Internet Services: TCP server/client, UDP client, DNS, Ping, HTTP client, FTP client, MQTT client Secure Connection with TLS/DTLS Secure boot Dimensions 66 x 25.4 mm Operating temperature -40° C to +85° C (-104° F to 185°F) Downloads Datasheet Schematics

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The SparkFun JetBot AI Kit V3.0 is a great launchpad for creating entirely new AI projects for makers, students, and enthusiasts interested in learning AI and building fun applications. It’s straightforward to set up and use and is compatible with many popular accessories. Several interactive tutorials show you how to harness AI's power to teach the SparkFun JetBot to follow objects, avoid collisions, and more. The Jetson Nano Developer Kit (not included in this kit) offers useful tools like the Jetson GPIO Python library and is compatible with standard sensors and peripherals; including some new python compatibility with the SparkFun Qwiic ecosystem. Additionally, the included image is delivered with the advanced functionality of JetBot ROS (Robot Operating System) and AWS RoboMaker Ready with AWS IoT Greengrass already installed. SparkFun’s JetBot AI Kit is the only kit currently on the market ready to move beyond the standard JetBot examples and into the world of connected and intelligent robotics. This kit includes everything you need to get started with JetBot minus a Phillips head screwdriver and an Ubuntu desktop GUI. If you need these, check out the includes tabs for some suggestions from our catalogue. Please be aware that the ability to run multiple neural networks in parallel may only be possible with a full 5V-4A power supply. Features SparkFun Qwiic ecosystem for I²C communication The ecosystem can be expanded using 4x Qwiic connectors on GPIO header Example Code for Basic Motion, Teleoperation, Collision avoidance, & Object Following Compact form factor to optimize existing neural net from NVIDIA 136° FOV camera for machine vision Pre-flashed MicroSD card Chassis assembly offers expandable architecture No soldering required Included 64 GB MicroSD card - pre-flashed SparkFun JetBot image: Nvidia Jetbot base image with the following installed: SparkFun Qwiic python library package Driver for Edimax WiFi adapter Greengrass Jetbot ROS Leopard Imaging 136FOV wide-angle camera & ribbon cable EDIMAX WiFi Adapter SparkFun Qwiic Motor Driver SparkFun Micro OLED Breakout (Qwiic) All hardware & prototyping electronics needed to complete your fully functional robot! Required NVIDIA Jetson Nano Developer Kit Downloads Assembly Guide

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