Search results for "wch OR ch32v307v OR evt OR r1 OR risc OR v OR development OR board"

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

Read more less

The LuckFox Pico Ultra is a compact single-board computer (SBC) powered by the Rockchip RV1106G3 chipset, designed for AI processing, multimedia, and low-power embedded applications. It comes equipped with a built-in 1 TOPS NPU, making it ideal for edge AI workloads. With 256 MB RAM, 8 GB onboard eMMC storage, integrated WiFi, and support for the LuckFox PoE module, the board delivers both performance and versatility across a wide range of use cases. Running Linux, the LuckFox Pico Ultra supports a variety of interfaces – including MIPI CSI, RGB LCD, GPIO, UART, SPI, I²C, and USB – providing a simple and efficient development platform for applications in smart home, industrial control, and IoT. Specifications Chip Rockchip RV1106G3 Processor Cortex-A7 1.2 GHz Neural Network Processor (NPU) 1 TOPS, supports int4, int8, int16 Image Processor (ISP) Max input 5M @30fps Memory 256 MB DDR3L WiFi + Bluetooth 2.4GHz WiFi-6 Bluetooth 5.2/BLE Camera Interface MIPI CSI 2-lane DPI Interface RGB666 PoE Interface IEEE 802.3af PoE Speaker interface MX1.25 mm USB USB 2.0 Host/Device GPIO 30 GPIO pins Ethernet 10/100M Ethernet controller and embedded PHY Default Storage Medium eMMC (8 GB) Included 1x LuckFox Pico Ultra W 1x LuckFox PoE module 1x IPX 2.4G 2 db antenna 1x USB-A to USB-C cable 1x Screws pack Downloads Wiki

Read more less

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.

Read more less

The ATmega328 Uno Development Board (Arduino Uno compatible) is a microcontroller board based on the ATmega328. It has 14 digital input/output pins (of which 6 can be used as PWM outputs), 6 analogue inputs, a 16 MHz ceramic resonator, a USB connection, a power jack, an ICSP header and a reset button. It contains everything needed to support the microcontroller; connect it to a computer with a USB cable or power it with a AC-to-DC adapter or battery to get started. Specifications Microcontroller ATmega328 Operating voltage 5 V DC Input voltage (recommended) 7-12 V DC Input voltage (limits) 6-20 V DC Digital I/O pins 14 (of which 6 provide PWM output) Analogue input pins 6 SRAM 2 kB (ATmega328) EEPROM 1 kB (ATmega328) Flash memory 32 kB (ATmega328) of which 0.5 kB used by bootloader Clock speed 16 MHz Downloads Manual

Read more less

The FRDM-MCXN947 is a compact and versatile development board designed for rapid prototyping with MCX N94 and N54 microcontrollers. It features industry-standard headers for easy access to the MCU's I/Os, integrated open-standard serial interfaces, external flash memory, and an onboard MCU-Link debugger. Specifications Microcontroller MCX-N947 Dual Arm Cortex-M33 cores @ 150 MHz each with optimized performance efficiency, up to 2 MB dual-bank flash with optional full ECC RAM, External flash Accelerators: Neural Processing Unit, PowerQuad, Smart DMA, etc. Memory Expansion *DNP Micro SD card socket Connectivity Ethernet Phy and connector HS USB-C connectors SPI/I²C/UART connector (PMOD/mikroBUS, DNP) WiFi connector (PMOD/mikroBUS, DNP) CAN-FD transceiver Debug On-board MCU-Link debugger with CMSIS-DAP JTAG/SWD connector Sensor P3T1755 I³C/I²C Temp Sensor, Touch Pad Expansion Options Arduino Header (with FRDM expansion rows) FRDM Header FlexIO/LCD Header SmartDMA/Camera Header Pmod *DNP mikroBUS User Interface RGB user LED, plus Reset, ISP, Wakeup buttons Included 1x FRDM-MCXN947 Development Board 1x USB-C Cable 1x Quick Start Guide Downloads Datasheet Block diagram

Read more less

Build your own AI microcontroller applications from scratch The MAX78000FTHR from Maxim Integrated is a small development board based on the MAX78000 MCU. The main usage of this board is in artificial intelligence applications (AI) which generally require large amounts of processing power and memory. It marries an Arm Cortex-M4 processor with a floating-point unit (FPU), convolutional neural network (CNN) accelerator, and RISC-V core into a single device. It is designed for ultra-low power consumption, making it ideal for many portable AI-based applications. This book is project-based and aims to teach the basic features of the MAX78000FTHR. It demonstrates how it can be used in various classical and AI-based projects. Each project is described in detail and complete program listings are provided. Readers should be able to use the projects as they are, or modify them to suit their applications. This book covers the following features of the MAX78000FTHR microcontroller development board: Onboard LEDs and buttons External LEDs and buttons Using analog-to-digital converters I²C projects SPI projects UART projects External interrupts and timer interrupts Using the onboard microphone Using the onboard camera Convolutional Neural Network

Read more less

This bundle contains: Book: Get Started with the NXP FRDM-MCXN947 Development Board (normal price: €40) NXP FRDM-MCXN947 Development Board (normal price: €30) Book: Get Started with the NXP FRDM-MCXN947 Development Board Develop projects on connectivity, graphics, machine learning, motor control, and sensors This book is about the use of the FRDM-MCXN947 Development Board, developed by NXP Semiconductors. It integrates the dual Arm Cortex-M33, operating at up to 150 MHz. Ideal for Industrial, IoT, and machine learning applications. It features Hi-Speed USB, CAN 2.0, I³C and 10/100 Ethernet. The board includes an on-board MCU-Link debugger, FlexI/O for LCD control, and dual-bank flash for read-while-write operations, supporting large external serial memory configurations. One of the important features of the development board is that it features an integrated eIQ Neutron Neural Processing Unit (NPU), thus enabling users to develop AI-based projects. The development board also supports Arduino Uno form factor header pins, making it compatible with many Arduino shields, mikroBUS connector for MikroElektronika Click Boards, and Pmod connector. One of the nice things of the FRDM-MCXN947 development board is that it includes several on-board debug probes, allowing programmers to debug their programs by communicating directly with the MCU. With the help of the debugger, programmers can single-step through a program, insert breakpoints, view and modify variables and so on. Many working and tested projects have been developed in the book using the popular MCUXpresso IDE and the SDK with various sensors and actuators. Use of the popular CMSIS-DSP library is also explained with several commonly used matrix operations. The projects provided in the book can be used without any modifications in many applications. Alternatively, readers can base their projects on those given in the book during the development of their own projects. NXP FRDM-MCXN947 Development Board The FRDM-MCXN947 is a compact and versatile development board designed for rapid prototyping with MCX N94 and N54 microcontrollers. It features industry-standard headers for easy access to the MCU's I/Os, integrated open-standard serial interfaces, external flash memory, and an onboard MCU-Link debugger. Specifications Microcontroller MCX-N947 Dual Arm Cortex-M33 cores @ 150 MHz each with optimized performance efficiency, up to 2 MB dual-bank flash with optional full ECC RAM, External flash Accelerators: Neural Processing Unit, PowerQuad, Smart DMA, etc. Memory Expansion *DNP Micro SD card socket Connectivity Ethernet Phy and connector HS USB-C connectors SPI/I²C/UART connector (PMOD/mikroBUS, DNP) WiFi connector (PMOD/mikroBUS, DNP) CAN-FD transceiver Debug On-board MCU-Link debugger with CMSIS-DAP JTAG/SWD connector Sensor P3T1755 I³C/I²C Temp Sensor, Touch Pad Expansion Options Arduino Header (with FRDM expansion rows) FRDM Header FlexIO/LCD Header SmartDMA/Camera Header Pmod *DNP mikroBUS User Interface RGB user LED, plus Reset, ISP, Wakeup buttons Included 1x FRDM-MCXN947 Development Board 1x USB-C Cable 1x Quick Start Guide Downloads Datasheet Block diagram

Read more less

The OKdo E1 is an ultra-low-cost Development Board based on the NXP LPC55S69JBD100 dual-core Arm Cortex-M33 microcontroller. The E1 board is perfect for Industrial IoT, building control and automation, consumer electronics, general embedded and secure applications. Features Processor with Arm TrustZone, Floating Point Unit (FPU) and Memory Protection Unit (MPU) CASPER Crypto co-processor to enable hardware acceleration for certain asymmetric cryptographic algorithms PowerQuad Hardware Accelerator for fixed and floating point DSP functions SRAM Physical Unclonable Function (PUF) for key generation, storage and reconstruction PRINCE module for real-time encryption and decryption of flash data AES-256 and SHA2 engines Up to Nine Flexcomm interfaces. Each Flexcomm interface can be selected by software to be a USART, SPI, I²C, and I²S interface USB 2.0 High-Speed Host/Device controller with on-chip PHY USB 2.0 Full-Speed Host/Device controller with on-chip PHY Up to 64 GPIOs Secure digital input/output (SD/MMC and SDIO) card interface Specifications LPC55S69JBD100 640kbyte flash microcontroller In-built CMSIS-DAP v1.0.7 debugger based on LPC11U35 Internal PLL support up to 100MHz operation, 16MHz can be mounted for full 150MHz operation. SRAM 320kB 32kHz crystal for real-time clock 4 user switches 3-colour LED User USB connector 2-off 16-way expansion connectors UART over USB virtual COM port

Read more less

The EC200U-EU C4-P01 development board features the EC200U-EU LTE Cat 1 wireless communication module, offering a maximum data rate of up to 10 Mbps for downlink and 5 Mbps for uplink. It supports multi-mode and multi-band communication, making it a cost-effective solution. The board is designed in a compact and unified form factor, compatible with the Quectel multi-mode LTE Standard EC20-CE. It includes an onboard USB-C port, allowing for easy development with just a USB-C cable. Additionally, the board is equipped with a 40-pin GPIO header that is compatible with most Raspberry Pi HATs. Features Equipped with EC200U-EU LTE Cat 1 wireless communication module, multi-mode & multi-band support Onboard 40-Pin GPIO header, compatible with most Raspberry Pi HATs 5 LEDs for indicating module operating status Supports TCP, UDP, PPP, NITZ, PING, FILE, MQTT, NTP, HTTP, HTTPS, SSL, FTP, FTPS, CMUX, MMS protocols, etc. Supports GNSS positioning (GPS, GLONASS, BDS, Galileo, QZSS) Onboard Nano SIM card slot and eSIM card slot, dual card single standby Onboard MIPI connector for connecting MIPI screen and is fully compatible with Raspberry Pi peripherals Onboard camera connector, supports customized SPI cameras with a maximum of 300,000 pixels Provides tools such as QPYcom, Thonny IDE plugin, and VSCode plugin, etc. for easy learning and development Comes with online development resources and manual (example in QuecPython) Specifications Applicable Regions Europe, Middle East, Africa, Australia, New Zealand, Brazil LTE-FDD B1, B3, B5, B7, B8, B20, B28 LTE-TDD B38, B40, B41 GSM / GPRS / EDGE GSM: B2, B3, B5, B8 GNSS GPS, GLONASS, BDS, Galileo, QZSS Bluetooth Bluetooth 4.2 (BR/EDR) Wi-Fi Scan 2.4 GHz 11b (Rx) CAT 1 LTE-FDD: DL 10 Mbps; UL 5 Mbps LTE-TDD: DL 8.96 Mbps; UL 3.1 Mbps GSM / GPRS / EDGE GSM: DL 85.6 Kbps; UL 85.6 Kbps USB-C Port Supports AT commands testing, GNSS positioning, firmware upgrading, etc. Communication Protocol TCP, UDP, PPP, NITZ, PING, FILE, MQTT, NTP, HTTP, HTTPS, SSL, FTP, FTPS, CMUX, MMS SIM Card Nano SIM and eSIM, dual card single standby Indicator P01: Module Pin 1, default as EC200A-XX PWM0 P05: Module Pin 5, NET_MODE indicator SCK1: SIM1 detection indicator, lights up when SIM1 card is inserted SCK2: SIM2 detection indicator, lights up when SIM2 card is inserted PWR: Power indicator Buttons PWK: Power ON/OFF RST: Reset BOOT: Forcing into firmware burning mode USB ON/OFF: USB power consumption detection switch Antenna Connectors LTE main antenna + DIV / WiFi (scanning only) / Bluetooth antenna + GNSS antenna Operating Temperature −30~+75°C Storage Temperature −45~+90°C Downloads Wiki Quectel Resources

Read more less

The CubeCell series is designed primarily for LoRa/LoRaWAN node applications. Built on the ASR605x platform (ASR6501, ASR6502), these chips integrate the PSoC 4000 series MCU (ARM Cortex-M0+ Core) with the SX1262 module. The CubeCell series offers seamless Arduino compatibility, stable LoRaWAN protocol operation, and straightforward connectivity with lithium batteries and solar panels. The HTCC-AB02S is a developer-friendly board with an integrated AIR530Z GPS module, ideal for quickly testing and validating communication solutions. Features Arduino compatible Based on ASR605x (ASR6501, ASR6502), those chips are already integrated the PSoC 4000 series MCU (ARM Cortex M0+ Core) and SX1262 LoRaWAN 1.0.2 support Ultra low power design, 21 uA in deep sleep Onboard SH1.25-2 battery interface, integrated lithium battery management system (charge and discharge management, overcharge protection, battery power detection, USB/battery power automatic switching) Good impendence matching and long communication distance Onboard solar energy management system, can directly connect with a 5.5~7 V solar panel Micro USB interface with complete ESD protection, short circuit protection, RF shielding, and other protection measures Integrated CP2102 USB to serial port chip, convenient for program downloading, debugging information printing Onboard 0.96-inch 128x64 dot matrix OLED display, which can be used to display debugging information, battery power, and other information Using Air530 GPS module with GPS/Beidou Dual-mode position system support Specifications Main Chip ASR6502 (48 MHz ARM Cortex-M0+ MCU) LoRa Chipset SX1262 Frequency 863~870 MHz Max. TX Power 22 ±1 dBm Max. Receiving Sensitivity −135 dBm Hardware Resource 2x UART1x SPI2x I²C1x SWD3x 12-bit ADC input8-channel DMA engine16x GPIO Memory 128 Kb FLASH16 Kb SRAM Power consumption Deep sleep 21 uA Interfaces 1x Micro USB1x LoRa Antenna (IPEX)2x (15x 2.54 Pin header) + 3x (2x 2.54 Pin header) Battery 3.7 V lithium battery (power supply and charging) Solar Energy VS pin can be connected to 5.5~7 V solar panel USB to Serial Chip CP2102 Display 0.96" OLED (128 x 64) Operating temperature −20~70°C Dimensions 55.9 x 27.9 x 9.5 mm Included 1x CubeCell HTCC-AB02S Development Board 1x Antenna 1x 2x SH1.25 battery connector Downloads Datasheet Schematic GPS module (Manual) Quick start GitHub

Read more less

PÚCA DSP is an open-source, Arduino-compatible ESP32 development board for audio and digital signal processing (DSP) applications with expansive audio-processing features. It provides audio inputs, audio outputs, a low-noise microphone array, an integrated test-speaker option, additional memory, battery-charge management, and ESD protection all on a small, breadboard-friendly PCB. Synthesizers, Installations, Voice UI, and More PÚCA DSP can be used for a wide range of DSP applications, including but not limited to those in the fields of music, art, creative technology, and adaptive technology. Music-related examples include digital-music synthesis, mobile recording, Bluetooth speakers, wireless line-level directional microphones, and the design of smart musical instruments. Art-related examples include acoustic sensor networks, sound-art installations, and Internet-radio applications. Examples related to creative and adaptive technology include voice user interface (VUI) design and Web audio for the Internet of Sounds. Compact, Integrated Design PÚCA DSP was designed for portability. When used with an external 3.7 V rechargeable battery, it can be deployed almost anywhere or integrated into just about any device, instrument, or installation. Its design emerged from months of experimentation with various ESP32 development boards, DAC breakout boards, ADC breakout boards, Microphone breakout boards, and audio-connector breakout boards, and – despite its diminutive size – it manages to provide all of that functionality in a single board. And it dos so without compromising signal quality. Specifications Processor & Memory Espressif ESP32 Pico D4 Processor 32-bit dual core 80 MHz / 160 MHz / 240 MHz 4 MB SPI Flash with 8 MB additional PSRAM (Original Edition) Wireless 2.4 GHz Wi-Fi 802.11b/g/n Bluetooth BLE 4.2 3D Antenna Audio Wolfson WM8978 Stereo Audio Codec Audio Line In on 3.5 mm stereo onnector Audio Headphone / Line Out on 3.5 mm stereo connector Stereo Aux Line In, Audio Mono Out routed to GPIO Header 2x Knowles SPM0687LR5H-1 MEMS Microphones ESD protection on all audio inputs and outputs Support for 8, 11.025, 12, 16, 22.05, 24, 32, 44.1 and 48 kHz sample rates 1 W Speaker Driver, routed to GPIO Header DAC SNR 98 dB, THD -84 dB (‘A’ weighted @ 48 kHz) ADC SNR 95 dB, THD -84 dB (‘A’ weighted @ 48 kHz) Line input impedance: 1 MOhm Line output impedance: 33 Ohm Form Factor and Connectivity Breadboard friendly 70 x 24 mm 11x GPIO pins broken out to 2.54 mm pitch header, with access to both ESP32 ADC channels, JTAG and capacitive touch pins USB 2.0 over USB Type C connector Power 3.7/4.2 V Lithium Polymer Rechargeable Battery, USB or external 5 V DC power source ESP32 and Audio Codec can be placed into low power modes under software control Battery voltage level detection ESD protection on USB data bus Downloads GitHub Datasheet Links Crowd Supply Campaign (includes FAQs) Hardware Overview Programming the Board The Audio Codec

Read more less

Build your own AI microcontroller applications from scratch The MAX78000FTHR from Maxim Integrated is a small development board based on the MAX78000 MCU. The main usage of this board is in artificial intelligence applications (AI) which generally require large amounts of processing power and memory. It marries an Arm Cortex-M4 processor with a floating-point unit (FPU), convolutional neural network (CNN) accelerator, and RISC-V core into a single device. It is designed for ultra-low power consumption, making it ideal for many portable AI-based applications. This book is project-based and aims to teach the basic features of the MAX78000FTHR. It demonstrates how it can be used in various classical and AI-based projects. Each project is described in detail and complete program listings are provided. Readers should be able to use the projects as they are, or modify them to suit their applications. This book covers the following features of the MAX78000FTHR microcontroller development board: Onboard LEDs and buttons External LEDs and buttons Using analog-to-digital converters I²C projects SPI projects UART projects External interrupts and timer interrupts Using the onboard microphone Using the onboard camera Convolutional Neural Network

Read more less