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.

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AI Brick Phone Mic

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.

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

Bluetooth, WiFi 802.11b/g/n, Bluetooth v5.0 Transceiver Module 2.4GHz PCB Trace Surface Mount The ESP32-S3-WROOM-1-N16R8 is a high-performance Wi-Fi + Bluetooth Low Energy (BLE) module developed by Espressif Systems. It is built around the ESP32-S3 SoC, featuring a dual-core Xtensa LX7 32-bit processor running up to 240 MHz. This module integrates 16 MB Flash memory and 8 MB PSRAM, making it suitable for memory-intensive applications such as AI, image processing, and advanced IoT systems. It also includes an onboard PCB trace antenna, RF circuitry, crystal oscillator, and power management components—allowing designers to quickly integrate wireless connectivity into compact embedded designs. Key Features Processing & Memory Dual-core Xtensa LX7 CPU, up to 240 MHz 384 KB ROM, 512 KB SRAM + 16 KB RTC SRAM 16 MB Flash (Quad SPI) 8 MB PSRAM (Octal/Quad SPI) Connectivity 2.4 GHz Wi-Fi (802.11 b/g/n) Bluetooth 5 (LE) + Mesh support Integrated PCB antenna Peripherals & Interfaces Up to 36 GPIOs Interfaces: UART, SPI, I2C, I2S, PWM, ADC, USB OTG Built-in USB Serial/JTAG support Supports touch sensors, timers, watchdogs, CAN (TWAI) Electrical Characteristics Supply voltage: 3.0 V – 3.6 V TX power: up to ~20.5 dBm RX sensitivity: ~-103.5 dBm Operating temp: −40 °C to +65 °C (typical) Advanced Capabilities Optimized for AI acceleration (vector instructions) Suitable for voice recognition, image processing, and edge AI Low-power modes for battery-operated devices| Typical Applications IoT devices and sensor hubs Smart home & home automation AIoT (voice/image recognition) Industrial automation & monitoring Wearables and health devices USB-connected embedded systems #Module #RF-Transceiver #ESP32-S3

SDRAM - Mobile LPDDR4X Memory IC 8Gbit Parallel 2.133 GHz 200-FBGA (10x15) The IM8G32L4JCBG-046I is an 8Gb (1GB) LPDDR4X SDRAM memory device designed for high-performance, low-power embedded applications. Organized as 256M × 32 bits, it delivers data rates up to 4266 MT/s, making it suitable for industrial computing, AI edge devices, networking equipment, automotive systems, and other memory-intensive applications. The LPDDR4X architecture reduces power consumption while maintaining high bandwidth and reliable operation across industrial temperature ranges. Key Features 8Gb (Gigabit) LPDDR4X SDRAM Memory organization: 256M × 32 bits High-speed operation up to 4266 MT/s Low-power LPDDR4X interface for reduced energy consumption 32-bit data bus width Industrial operating temperature range: –40°C to +95°C 200-ball FBGA package (10 mm × 15 mm) High bandwidth for demanding embedded applications Optimized for low-power and thermally constrained designs Suitable for industrial, automotive, networking, and edge AI systems #LPDDR4X #SDRAM #MemoryIC #EmbeddedSystems #IndustrialElectronics #EdgeComputing #AIoT #HighSpeedMemory #LowPowerDesign #AutomotiveElectronics #NetworkingHardware #FBGA #HardwareDesign #ElectronicsEngineering #PCBDesign #IntelligentMemory

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

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

Wi-Fi® 4 + Bluetooth® 5 LE System-in-Package (SiP) MCU – Highly integrated 2.4 GHz wireless System-in-Package (SiP) featuring an ESP32-S3 dual-core Xtensa® LX7 microcontroller for IoT devices, smart home products, AIoT, edge computing, industrial automation, HMI, wearable devices, and embedded wireless applications. Operates at up to 240 MHz with 8 MB embedded Flash and 2 MB embedded PSRAM, eliminating the need for external memory and reducing PCB size. Supports Wi-Fi 802.11 b/g/n and Bluetooth® 5 LE (including Long Range and 2 Mbps PHY), with up to +20 dBm transmit power and 150 Mbps Wi-Fi data rate. Features native USB 2.0 OTG, vector instructions for AI acceleration, 45 programmable GPIOs, SPI, I²C, I²S, UART, USB, RMT, LCD/Camera interface, PWM, TWAI® (CAN), ADC, touch sensing, AES-XTS, SHA, RSA, ECC, HMAC, secure boot, Flash encryption, and a true random number generator (TRNG) for secure embedded applications. Operates from a 3.0 V to 3.6 V supply, over a −40°C to +85°C temperature range, and is housed in a compact 56-pin QFN (7 × 7 mm) package. #EspressifSystems #ESP32S3PICO1N8R2 #ESP32S3 #WirelessMCU #SystemInPackage #WiFi #Bluetooth5LE #DualCore #XtensaLX7 #USBOTG #AIoT #EmbeddedSystems

The Arduino Nicla Voice packs machine-learning capabilities on the edge into a tiny fingerprint. Implement always-on speech recognition with the Nicla Voice. The board integrates a dedicated Neural Decision Processor Syntiant NDP 120 able to run multiple AI algorithms at the same time. Leverage the built-in microphone, nRF52832 microcontroller, Bluetooth Low Energy module, 6-axis IMU and 3-axis magnetometer to create your own wireless sensor network for machine learning applications with low power consumption capabilities.

BGA-565(15.5x14.4) Microcontrollers, Quad-core ARM Cortex-A55 processor The RK3566 is a high-performance, low-power 64-bit application processor developed by Rockchip for AIoT, industrial control, smart displays, tablets, embedded systems, and single-board computers. It integrates a quad-core ARM Cortex-A55 CPU, Mali-G52 GPU, AI acceleration engine (NPU), advanced multimedia processing, and a rich set of connectivity interfaces, making it suitable for Linux- and Android-based applications requiring efficient performance and multimedia capabilities. Key Features Quad-core 64-bit ARM Cortex-A55 processor operating up to 2.0 GHz. ARM Mali-G52 2EE GPU with support for OpenGL ES 3.2, OpenCL 2.0, and Vulkan 1.1. Integrated NPU delivering up to 1 TOPS AI computing performance. Supports DDR3, DDR3L, DDR4, LPDDR3, LPDDR4, and LPDDR4X memory. Hardware video decoding up to 4K@60fps for H.264, H.265, and VP9 formats. Hardware video encoding up to 1080p@60fps for H.264 and H.265. Built-in 8MP ISP with HDR image processing support. Multiple display interfaces including HDMI 2.0, eDP, MIPI-DSI, LVDS, RGB, and E-Ink. High-speed connectivity with USB 3.0, USB 2.0, PCIe, SATA, Gigabit Ethernet, SDIO, and eMMC 5.1. Rich peripheral support including UART, SPI, I²C, PWM, ADC, I²S, PDM, and GPIO. Optimized for Android, Linux, industrial HMI, smart home, edge computing, and AIoT applications. Manufactured using a 22 nm process for improved power efficiency. #RK3566 #Rockchip #ARMCortexA55 #MaliG52 #AIoT #EmbeddedSystems #SingleBoardComputer #Linux #Android #IndustrialControl #SmartDisplay #EdgeComputing #SoC #Processor #NPU #4KVideo #IoT #Electronics #HardwareDesign #PCBDesign