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It is an MCU-based vision AI module powered by Arm Cortex-M55 & Ethos-U55. TensorFlow and PyTorch frameworks are supported. Compatible with Arduino IDE and no code model deployment and immediate visualization of identification results with SenseCraft AI.

It is an MCU-based vision AI module powered by Arm Cortex-M55 & Ethos-U55. TensorFlow and PyTorch frameworks are supported. Compatible with Arduino IDE and no code model deployment and immediate visualization of identification results with SenseCraft AI.

Spot the mistake! Learn how to use AI to conduct a design review on an ESP32-based control board. This project is ideal for autonomous or radio-controller robots featuring inputs for sensors, encoders, and a Flysky RC receiver, plus an I2C display for configuration.

Learn how to use AI Auto Layout on this ESP32 Espresso Smart Scale! In one click you’ll see AI Auto Layout perform magic. Pay close attention to how we recommend creating rulesets, zones, and fanouts. By copying the setup in this example on your own project, you’ll have a fully routed board in no time!

Edge Compact Fanless Embedded AI System with NVIDIA® Jetson Orin Nano™

Learn how to use Copilot, your AI design assistant, to brainstorm and develop a new idea from concept to custom board design. Discuss requirements, generate architectures, research parts, and draw your schematic.

PCB silkscreen logo of CyberBrain size 17x20mm #skral #ai #CyberBrain #logo

6-axis IMU (inertial measurement unit) with high-g accelerometer, embedded AI, and sensor fusion for high-end applications, car crash detection Accelerometer, Gyroscope, Magnetometer, 6 Axis Sensor I2C, SPI Output #CommonPartsLibrary #IntegratedCircuit #Sensor #Transducer #Motion-Sensor #IMUs #LSM6

PCB silkscreen logo of BB eye camera size 17x21mm #skral #ai

Multiple Function Sensor Modules BME690 is the gas sensor with Artificial Intelligence (AI) and integrated high-linearity and high-accuracy pressure, humidity and temperature sensors.

System On Chip (SOC) IC It integrates multiple processing units including CPUs, DSPs, AI accelerators, and GPU into a single chip to handle vision processing, deep learning, sensor fusion, and real-time control in automotive and industrial systems. • C7x floating point, vector DSP, up to 1.0GHz, 80 GFLOPS, 256 GOPS • Deep-learning matrix multiply accelerator (MMA), up to 8 TOPS (8b) at 1.0GHz • Vision Processing Accelerators (VPAC) with Image Signal Processor (ISP) and multiple vision assist accelerators • Depth and Motion Processing Accelerators (DMPAC) • Dual 64-bit Arm® Cortex®-A72 microprocessor subsystem at up to 2.0GHz – 1MB shared L2 cache per dual-core Cortex®- A72 cluster – 32KB L1 DCache and 48KB L1 ICache per Cortex®-A72 core • Six Arm® Cortex®-R5F MCUs at up to 1.0GHz – 16K I-Cache, 16K D-Cache, 64K L2 TCM – Two Arm® Cortex®-R5F MCUs in isolated MCU subsystem – Four Arm® Cortex®-R5F MCUs in general compute partition • Two C66x floating point DSP, up to 1.35GHz, 40GFLOPS, 160GOPS • 3D GPU PowerVR® Rogue 8XE GE8430, up to 750MHz, 96GFLOPS, 6Gpix/sec • Custom-designed interconnect fabric supporting near max processing entitlement Memory subsystem: • Up to 8MB of on-chip L3 RAM with ECC and coherency – ECC error protection – Shared coherent cache – Supports internal DMA engine • External Memory Interface (EMIF) module with ECC – Supports LPDDR4 memory types – Supports speeds up to 4266MT/s – 32-bit data bus with inline ECC • General-Purpose Memory Controller (GPMC) • 512KB on-chip SRAM in MAIN domain, protected by ECC #CommonPartsLibrary #IntegratedCircuit

IC RF TxRx + MCU Bluetooth, WiFi 802.11b/g/n, Bluetooth v5.0 2.412GHz ~ 2.484GHz 56-VFQFN Exposed Pad The ESP32-S3R8 is a high-performance wireless microcontroller system-on-chip manufactured by Espressif Systems. This device integrates dual-core processing, Wi-Fi connectivity, Bluetooth Low Energy communication, embedded memory resources, and advanced peripheral interfaces within a compact package optimized for embedded and IoT applications. The microcontroller is based on the Xtensa LX7 architecture and is designed to support edge computing, wireless communication, human-machine interfaces, audio processing, AI acceleration, and low-power connected systems. The ESP32-S3R8 includes integrated flash and RAM resources, advanced security functions, vector instruction acceleration, and extensive GPIO/peripheral capability for modern embedded development. The device is widely used in IoT devices, industrial automation systems, smart home equipment, wearable electronics, wireless sensor nodes, edge AI applications, USB-enabled embedded systems, and portable consumer electronics. Its integrated wireless functionality and high processing performance reduce external component count while simplifying system-level design for connected embedded platforms. Engineering Specification Device Type Wireless microcontroller system-on-chip Processor Architecture Dual-core Xtensa LX7 microcontroller architecture Wireless Connectivity Integrated Wi-Fi and Bluetooth Low Energy communication Processing Features High-performance embedded processing with vector instruction acceleration Memory Resources Integrated RAM and embedded memory architecture Communication Interfaces SPI I2C UART I2S USB PWM ADC GPIO interfaces Wireless Features Secure wireless networking and low-power communication support USB Capability Integrated USB communication and device functionality AI and DSP Features Vector instruction support for AI and digital signal processing workloads Security Features Hardware encryption and secure boot support Power Characteristics Low-power operating modes for battery-powered systems Package Type QFN surface-mount package Mounting Style Surface mount technology Applications IoT devices Wireless embedded systems Industrial automation Smart home electronics Edge AI applications Wearable devices Consumer electronics USB-enabled systems Sensor networks Embedded communication platforms Manufacturer Espressif Systems #commonpartslibrary #esp32 #esp32s3 #wirelessmcu #microcontroller #iot #embeddedhardware #wifi #bluetoothlowenergy #espressif #surfaceountcomponents #electronicsdesign #edgeai #wirelesscommunication #consumerelectronics

Coral Accelerator Module a solderable multi-chip module including the Edge TPU Coral Google Edge TPU and PMIC G313-06329-00 #AI #Coral #TensorFlow #google

The Bosch BME688 is a state-of-the-art digital low power gas, pressure, temperature, and humidity sensor that integrates Artificial Intelligence (AI) capabilities, making it the first of its kind in the market. Housed in a compact 3.0 x 3.0 x 0.9 mm³ metal lid LGA package, it is designed to meet the demands of mobile and connected applications where size and power consumption are critical factors. The sensor is capable of detecting Volatile Organic Compounds (VOCs), volatile sulfur compounds (VSCs), carbon monoxide, and hydrogen in the part per billion (ppb) range. Building on the features of the BME680, the BME688 introduces a gas scanner function that enhances its sensitivity, selectivity, data rate, and power consumption for specific applications. With the help of Bosch AI-Studio tool, customers can train the BME688 gas scanner for their specific needs, making it an ideal choice for a wide range of applications including indoor air quality measurement, detection of bad breath or spoiled food, early odor detection, and smart home devices among others. The BME688 operates within a supply voltage range of 1.71 V to 3.6 V and offers various modes of operation to balance power consumption and measurement responsiveness, catering to both portable and stationary applications.

WiFi 802.11a/b/g/n, Bluetooth v5.0 Transceiver Module 2.4GHz PCB Trace The ESP32-S3-WROOM-1-N8R2 is a compact, low-power Wi-Fi and Bluetooth® Low Energy (BLE) module developed by Espressif Systems. It is based on the ESP32-S3 system-on-chip (SoC), which integrates a dual-core Xtensa® LX7 processor optimized for high performance and edge AI processing. This module includes 8 MB of external SPI flash memory and 2 MB of PSRAM, enabling efficient handling of memory-intensive applications such as graphical interfaces, buffering, and embedded machine learning workloads. Designed for flexibility and scalability, the module integrates RF components, power management, and a wide range of peripherals into a surface-mount package suitable for IoT, industrial, and consumer electronics applications. Key Features Dual-core Xtensa® LX7 processor operating up to 240 MHz Integrated 2.4 GHz Wi-Fi (802.11 b/g/n) Bluetooth 5 Low Energy support Embedded 8 MB SPI flash memory Integrated 2 MB PSRAM AI acceleration through vector instruction support USB OTG (full-speed) capability Multiple low-power operating modes Built-in hardware security features Extensive peripheral interface support Functional Overview The module consists of several integrated subsystems, including a dual-core processing unit, memory subsystem (flash and PSRAM), RF subsystem for wireless communication, peripheral interface controllers, power management circuitry, and a hardware-based security engine. Electrical Characteristics Operating voltage range: 3.0 V to 3.6 V (typical 3.3 V) Operating temperature range: -40°C to +85°C RF operating frequency: 2.4 GHz Current consumption varies depending on operating mode, ranging from microamp levels in deep sleep to hundreds of milliamps during active transmission Processor and Memory The module features a dual-core Xtensa® LX7 CPU capable of running at frequencies up to 240 MHz. It includes approximately 512 KB of internal SRAM, supplemented by 8 MB of external flash memory and 2 MB of PSRAM for extended data storage and processing. Wireless Connectivity The ESP32-S3-WROOM-1-N8R2 supports Wi-Fi communication compliant with 802.11 b/g/n standards in the 2.4 GHz band. It also supports Bluetooth 5 Low Energy for short-range wireless communication. The module includes an integrated PCB antenna and supports RF output power up to approximately +20 dBm. Peripheral Interfaces The module provides a wide range of interfaces, including general-purpose input/output (GPIO) pins, SPI, I2C, UART, and I2S for audio applications. It also supports PWM for LED control, a 12-bit analog-to-digital converter (ADC), and USB OTG functionality. Pin functions are multiplexed to maximize flexibility. Power Management Power efficiency is achieved through multiple operating modes, including active mode, modem sleep, light sleep, and deep sleep. The module includes an RTC subsystem for low-power timekeeping and supports dynamic frequency scaling to optimize performance and energy consumption. Security Features The module incorporates several hardware-based security mechanisms, including secure boot, flash encryption, and digital signature verification. It also includes a hardware random number generator and cryptographic accelerators supporting AES, SHA, RSA, and ECC algorithms. Mechanical Characteristics The module is designed for surface-mount integration and measures approximately 18 mm by 25.5 mm. It includes an onboard PCB antenna and is suitable for compact embedded designs. Pin Configuration Overview GPIO pins are multiplexed to support various peripheral functions such as analog inputs, communication interfaces, and control signals. Dedicated pins are provided for power supply, module enable, and boot configuration. Typical Applications Internet of Things (IoT) devices Smart home systems Industrial automation and monitoring Edge AI and machine learning applications Wearable electronics Audio and multimedia systems USB-enabled embedded devices Compliance The module is designed to meet Wi-Fi and Bluetooth standards and is compliant with RoHS requirements. Certification such as FCC or CE may apply depending on the specific module variant and deployment. Ordering Information The ESP32-S3-WROOM-1-N8R2 variant includes 8 MB of flash memory and 2 MB of PSRAM. #commonpartslibrary #integratedcircuit #transceiver #wireless #rf

RV1106 is a Rockchip AI vision SoC designed for smart cameras and edge AI applications. It integrates a CPU + ISP + NPU, enabling real-time video processing, AI inference (like face/object detection), and low-power operation in compact embedded systems. #Microcontroller