🍓【Powful CPU】The CPU of the Raspberry Pi 4 Model B adopts the latest ARM Cortex-A72 architecture, which is also used in high-performance smartphones, and has evolved into a real PC.The operating clock has been changed from Pi3's 1.2GHz to 1.5GHz, and the speed has become a different dimension with the updated architecture. | 🍓【Video output/GPU】The on-board GPU of the Raspberry Pi 4 supports 4Kp@60 and newly supports H.265 decoding, OpenGL ES 3.0, etc.As for the video output, two micro HDMIs with smaller connectors are installed, and the Raspberry Pi 4 also supports dual screen output. | 🍓【USB 3.0】With a new SoC, the speed of the Raspberry Pi 4 around I/O has been improved, and finally USB 3.0 is supported.USB boot is faster and more convenient. | 🍓【network&Bluetooth】Gigabit Ethernet (wired LAN) has also been significantly speeded up from 300Mbps of Pi 3B + to 1000Mbps (logical value).In addition, Bluetooth supported version has been upgraded to 5.0, and the transfer speed of Pi 4 has been doubled. | 🍓【Power input connector】The power input connector of the Raspberry Pi 4 has been changed to USB type C. It is easier to use than micro USB and can supply a larger current reliably.The power requirement of Raspberry Pi 4 Model B is 5V 3.0A, which is higher than the previous model.

Performs high-speed ML inferencing: Each Edge TPU coprocessor is capable of performing 4 trillion operations per second (4 TOPS), using 2 watts of power. For example, it can execute state-of-the-art mobile vision models such as MobileNet v2 at almost 400 FPS, in a power-efficient manner. With the two Edge TPUs in this module, you can double the inferences per second (8 TOPS) in several ways, such as by running two models in parallel or pipelining one model across both Edge TPUs. | Works with Debian Linux and Windows: Integrates with Debian-based Linux or Windows 10 systems with a compatible card module slot. | Supports TensorFlow Lite: No need to build models from the ground up. TensorFlow Lite models can be compiled to run on the Edge TPU. | Supports AutoML Vision Edge: Easily build and deploy fast, high-accuracy custom image classification models to your device with AutoML Vision Edge. Description

Performs high-speed ML inferencing: High-speed TensorFlow Lite inferencing with low power, small footprint, local inferencing | Supports all major platforms: Connects via USB 3.0 Type-C to any system running Debian Linux (including Raspberry Pi), macOS, or Windows 10 | Supports TensorFlow Lite: no need to build models from the ground up. Tensorflow Lite models can be compiled to run on the edge TPE | Supports AutoML Vision Edge: easily build and deploy fast, high-accuracy custom image classification models at the edge. | Compatible with Google Cloud

🌱Small and flexible Raspberry Pi microcontroller: Equip with featured tiny RP2040 microcontroller chip with 30 GPIO pins | 🌱Wireless Connection Supported: Incorporate Wi-Fi IEEE 802.11 b/g/n wireless LAN, as well as Bluetooth 5.2 connection | 🌱Relatively low price for high performance: Best price ratio for one wireless microcontroller represented by Raspberry Pi | 🌱 Simple easy to use: Drag & drop programming using mass storage over a USB through MicroPython | 🌱Designed for beginners/children: Provide tons of projects/tutorials, allowing for quick positive programming feedback, getting started well with electronics

Compact Linux Development Board: Equipped with a 1GHz ARM Cortex-A7 processor supporting Raspberry Pi OS, with a size of only 65mm x 30mm x 5mm | Ready-to-use: Mounted with headers and ready for use | Wireless Connection: Built-in 802.11n Wi-Fi and Bluetooth 4.1 | 40-pins compatible Raspberry Pi: Compatible with connecting sensors, actuators, and other electronic components | Extended Memory: Utilize 512MB of LPDDR2 SDRAM and a microSD card as the primary storage medium

📟【Frequency Modulated Continuous Wave】This mmWave applies Doppler radar technology with Near Distance Sensor(NDS) operating at 24GHz. Infineon mmWave FMCW industrial radar. | 📟【Anonymous Detection】For privacy protection, the radar uses the properties of millimeter waves that only process wave signals to provide a fully private sensing environment. | 📟【High Stability】Not affected by environmental conditions such as temperature, dust, snow, light, etc. | 📟【Harmless Working Status】Output 10 dBm harmless energy power. | 📟【High Flexibility】The radar supports secondary development and adapts to various scenarios applications as it includes scene recognition capability.

💎Notice: When we produced the new batch of CAN-BUS Shield V2, the wire of the back pads was embedded inside the PCB, although the wire between the pads is now not visible on the outside, the inside is still connected, if you want to change the wiring of the pads, you still need to cut the wiring in the PCB first. | 💎CAN-BUS is a common industrial bus because of its long travel distance, medium communication speed and high reliability. It is commonly found on modern machine tools and as an automotive diagnostic bus. Thanks for CAN-BUS, makers are able to hack their cars more conveniently. | 💎The CAN-BUS Shield V2 still uses MCP2515 as CAN-BUS controller and MCP2551 as CAN transceiver. OBD-II or CAN standard pinout can be selected by switching jumpers on DB9 interface, the default pinout is OBD-II. | 💎We add a TF card slot for data storage and the CS pin can be either set to D4 or D5. The INT pin can also be set to D2 or D3 by switching jumpers on the back of the shield. | 💎CAN BUS Shield Work well with Arduino UNO (ATmega328), Arduino Mega (ATmega1280/2560) as well as Arduino Leonardo (ATmega32U4) and LinkIt One.

●Powerful Pi 5: Latest credit card-sized computer with 4GB/8GB RAM options. 2.4GHz quad-core processor delivers 3x faster performance. | ●Instant Start: 128GB SD card with pre-installed Raspberry Pi OS - just plug and play. | ●Cool & Protected: Official Pi 5 case with advanced cooling system keeps your board running smoothly. | ●Reliable Power: 27W official power supply ensures stable, safe operation. | ●Quality Assured: Premium components with 1-year warranty and tech support. | ●Due to the product batch problem, the SD card will have two models randomly mixed. Both are pre-installed with Raspberry Pi OS

Worldwide leading Ultra-Low-Power AI Wi-Fi IP Camera SoC：8-in-1 SoC featuring embedded AI & NPU, High resolution up to 2K | Fast boot-up in milliseconds; ultra-low power in microampere | Supporting battery-powered, AI & IoT Ecosystems | Multiple streams real-time H.265/H.264/JPEG encoding | SDK supports free RTOS, IAR, GCC, Arduino IDE

Powerful MCU Board: Incorporate the ESP32S3 32-bit, dual-core, Xtensa processor chip operating up to 240 MHz, mounted multiple development ports, Arduino / MicroPython supported | Advanced Functionality: Detachable OV2640 camera sensor for 1600*1200 resolution, compatible with OV5640 camera sensor, integrating additional digital microphone | Great Memory for more Possibilities: Offer 8MB PSRAM and 8MB FLASH, supporting SD card slot for external 32GB FAT memory | Outstanding RF performance: Support 2.4GHz Wi-Fi and BLE dual wireless communication, support 100m+ remote communication when connected with U.FL antenna | Thumb-sized Compact Design: 21 x 17.5mm, adopting the classic form factor of XIAO, suitable for space-limited projects like wearable devices

🌱【Outstanding RF performance】 Powerful ESP32-C3 SoC and U.FL antenna provided that supports WiFi/Bluetooth connection over 100m. | 🌱【Rich Interface】 There are 11 digital I/O that can be used as PWM pins and 4 analog i/o that can be used as ADC pins. It supports UART, IIC, and SPI serial communication ports, also including IIS (Internet Information Services). | 🌱【Thumb-size Design】 21 x 17.5mm overall dimension, portable and lightweight. | 🌱【Low power consumption】 Lowest as 44 μA (deep sleep mode), with 4 working modes available. | 🌱【Onboard battery charge IC】 Supports battery charging, great for various wearable scenarios and wireless IoT applications.

Enhanced Connectivity: Combines 2.4GHz Wi-Fi 6 (802.11ax), Bluetooth 5(LE), and IEEE 802.15.4 radio connectivity, allowing you to apply the Thread and Zigbee protocols. | Matter Native: Supports building Matter-compliant smart home projects thanks to its enhanced connectivity, achieving interoperability | Security Encrypted on Chip: Powered by ESP32-C6, it brings enhanced encrypted-on-chip security to your smart home projects via secure boot, encryption, and Trusted Execution Environment (TEE) | Outstanding RF performance: Has an on-board antenna with up to 80m BLE/Wi-Fi range, while reserving an interface for external UFL antenna | Leveraging Power Consumption: Comes with 4 working modes, with the lowest being 15 μA in deep sleep mode, while also supporting lithium battery charge management. | Dual RISC-V Processors: Incorporates two 32-bit RISC-V processors, with the high-performance processor running up to 160 MHz, and the low-power processor clocking up to 20 | Classic XIAODesigns: Remains the classic XIAO designs of the thumb-size form factor of 21 x 17.5mm, and single-sided mount, making it perfect for space-limited projects such as wearables

Powerful MCU Board: Incorporate the ESP32S3 32-bit, dual-core, Xtensa processor running at up to 240MHz, mounted multiple development ports, Arduino / MicroPython supported | Outstanding RF performance: supports 2.4GHz WiFi and BLE 5.0 dual wireless communication, support 100m+ remote communication when connected with U.FL antenna | Elaborate Power Design: lithium battery charge management capability, offer 4 power consumption model which allows for deep sleep mode with power consumption as low as 14μA | Thumb-sized Compact Design: 21 x 17.5mm, adopting the classic form factor of XIAO, suitable for space limited projects like wearable devices | Perfect for Production: Breadboard-friendly & SMD design, no components on the back

🌱【Powerful CPU】 The Seeeduino XIAO is equipped with an ARM Cortex-M0+ 32bit 48MHz microcontroller, which is three times faster than Arduino Uno and Arduino Nano. Furthermore, this Arduino IDE compatible board XIAO has 256KB flash memory and 32KB SRAM. | 🌱【Rich Interfaces in a Tiny Size】 The device has 14 GPIO pins, each of which has 11 analog channels, 11 digital channels, I2C*1, UART*1, and SPI*1, USB Type-C interface*1 in a tiny space, just 20mm*17.5mm (about the size of your thumb). Seeeduino XIAO is the smallest Arduino compatible board in the Seeeduino series. | 🌱【Fully compatible with Arduino IDE】 Seeeduino XIAO development board is perfectly compatible with Arduino IDE and you can easily create small projects using the extensive and comprehensive Arduino library. It has a 2.54mm pin pitch and can be used even when inserted into a breadboard because it is an Arduino microcontroller.It has a 2.54mm pin pitch and can be used even when inserted into a breadboard because it is an Arduino microcontroller. | 🌱【Applications】 Seeeduino XIAO is suitable for Wearable devices, Rapid prototyping, DIY keyboard, USB to multi-channel TTL/USB host mode, etc. | 🌱【Perfect for Wearable and Tiny Arduino Projects】 This microcontroller has good performance in processing but needs less power. As a matter of fact, it is designed in a tiny size and can be used for Arduino wearable devices and small projects.

🌱【Powerful CPU】 The Seeeduino XIAO is equipped with an ARM Cortex-M0+ 32bit 48MHz microcontroller, which is three times faster than Arduino Uno and Arduino Nano. Furthermore, this Arduino IDE compatible board Xiao has 256KB flash memory and 32KB SRAM. | 🌱【Rich Interfaces in a Tiny Size】 The device has 14 GPIO pins, each of which has 11 analog channels, 11 digital channels, I2C*1, UART*1, and SPI*1, USB Type-C interface*1 in a tiny space, just 20mm*17.5mm (about the size of your thumb). Seeeduino XIAO is the smallest Arduino compatible board in the Seeeduino series. | 🌱【Fully compatible with Arduino IDE】 Seeeduino XIAO development board is perfectly compatible with Arduino IDE and you can easily create small projects using the extensive and comprehensive Arduino library. It has a 2.54mm pin pitch and can be used even when inserted into a breadboard because it is an Arduino microcontroller.It has a 2.54mm pin pitch and can be used even when inserted into a breadboard because it is an Arduino microcontroller. | 🌱【Applications】 Seeeduino XIAO is suitable for Wearable devices, Rapid prototyping, DIY keyboard, USB to multi-channel TTL/USB host mode, etc. | 🌱【Perfect for Wearable and Tiny Arduino Projects】 This microcontroller has good performance in processing but needs less power. As a matter of fact, it is designed in a tiny size and can be used for Arduino wearable devices and small projects.