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.

AI Brick Phone AMP

AI Brick Phone Mic

AI Brick Phone ADC

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.

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!

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.

Welcome to your new project. Imagine what you can build here.

Seeed Studio XIAO ESP32S3 Module Integration (Camera-Free)

The XIAO RP2350 packs the power of the Raspberry Pi RP2350 (switchable architecture of dual Arm Cortex-M33 cores running at 150MHz with FPU, and dual open-hardware Hazard3 RISC‑V cores, enhanced security and encryption) into the classic XIAO form factor. Measuring just 21x17.5mm, it features 19 multifunction GPIOs, an RGB LED, and a Battery Management System with ultra-low power consumption of 27μA, battery power supply, and direct battery voltage measurement. Thanks to the XIAO ecosystem, the XIAO RP2350 is compatible with a wide range of add-ons, including displays, LED matrix, Grove modules, CAN Bus, Vision AI sensors, and mmWave sensors. With native support for MicroPython, C, and C++, the XIAO RP2350 is perfect for developers of all levels looking to create compact, battery-powered applications for smart control, wearables, DIY keyboards, and more.

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

Bluetooth, WiFi 802.11b/g/n, Bluetooth v5.0 Transceiver Module 2.4GHz PCB Trace Surface Mount The ESP32-S3-WROOM-2-N32R16V is a powerful dual-core microcontroller module that integrates wireless connectivity, large memory, and hardware acceleration for AI and signal processing tasks. It is particularly suited for applications requiring edge AI, voice recognition, and high-speed data processing, while still maintaining low power consumption. Dual-core Xtensa LX7 CPU Up to 240 MHz Includes vector instructions for AI and DSP workloads Wi-Fi 2.4 GHz (802.11 b/g/n) Bluetooth 5 (LE) N32 → 32 MB external Flash R16 → 16 MB PSRAM Built for memory-intensive applications #commonpartslibrary #transceiver #wireless #rf

Arduino Nicla Voice Integration with HDMI Output for Edge AI

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

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

RF System on a Chip - SoC Cortex-M55 250MHz, 2.5D GPU, 4MB MRAM, 3.75MB SRAM, BLE5.4, -20 to +70 C, BGA , 1.71 V to 2.2 V -20C ~ 70C ARM® Cortex®-M55 System On Chip (SOC) IC Apollo510B 250MHz The AP510BFA-CBR is an ultra-low-power MCU System-on-Chip (SoC) designed for advanced embedded and edge-AI applications. It belongs to the Apollo510B series and integrates a powerful ARM Cortex-M55 processor optimized for both performance and energy efficiency. It combines processing, memory, and multiple peripherals into a single BGA package, making it suitable for compact and power-sensitive designs. Key Characteristics Core: ARM Cortex-M55 Max CPU Speed: 250 MHz Architecture: MCU / SoC Flash Memory: 4 MB RAM: ~3.75 MB Connectivity: I2C, SPI, UART, USB Wireless Support: Bluetooth 5.4 (variant dependent) Package: 153-BGA (compact high-density package) Key Features Built on Ambiq’s ultra-low-power SPOT technology Designed for battery-powered and energy-sensitive devices High computational performance for edge AI and DSP workloads Integrated peripherals for embedded system development Typical Applications Wearables (smartwatches, fitness bands) Smart home and IoT devices Edge AI / machine learning nodes Industrial sensors and monitoring systems Wireless communication modules #CommonPartsLibrary #IntegratedCircuit #SoC #Apollo510B

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

Seeed Studio XIAO ESP32S3 leverages dual-core ESP32S3 chip, supporting both Wi-Fi and BLE wireless connectivities, which allows battery charge. It integrates built-in camera sensor, digital microphone. It offers 8MB PSRAM, 8MB FLASH, and external SD card slot. All of these make it suitable for embedded ML, like intelligent voice and vision AI.

Seeed Studio XIAO ESP32S3 leverages dual-core ESP32S3 chip, supporting both Wi-Fi and BLE wireless connectivities, which allows battery charge. It integrates built-in camera sensor, digital microphone. It offers 8MB PSRAM, 8MB FLASH, and external SD card slot. All of these make it suitable for embedded ML, like intelligent voice and vision AI.

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.