The Coral System-on-Module (SoM) is a fully-integrated system that helps you build embedded devices that demand fast machine learning (ML) inferencing. It contains NXP’s iMX 8M system-on-chip (SoC), eMMC memory, LPDDR4 RAM, Wi-Fi, and Bluetooth, but its unique power comes from Google’s Edge TPU coprocessor for high-speed machine learning inferencing.
NXP i.MX 8M SoC
Quad-core ARM Cortex-A53, plus Cortex-M4F
2D/3D Vivante GC7000 Lite GPU and VPU
Google Edge TPU ML accelerator
Wi-Fi 2×2 MIMO (802.11b/g/n/ac 2.4/5 GHz)
HDMI and MIPI-DSI
Up to 95x GPIO (including SPI, I2C, PWM, UART, SAI, and SDIO)
Upload the compiled firmware to your device. If everything is fine, your thermometer box will send the sensor measurements to the cloud and you’ll see such nice graphs over time if enough measurements have accumulated.
This CANBed-FD adopts MCP2517FD CAN Bus controller with SPI interface and MCP2542FD CAN transceiver to achieve the CAN-BUS capability. With an OBD-II converter cable added on and the OBD-II library imported, you are ready to build an onboard diagnostic device.
Compact size (56x41mm)
Work at CAN-FD and CAN 2.0
Industrial standard 9 pin sub-D connector or 4-pin terminal
OBD-II and CAN standard pinout selectable at sub-D connector
2 x 4-Pin Grove connectors compatible with the Grove ecosystem
To install The IoT Guru integration into your Arduino IDE you can use the Library Manager (available from IDE version 1.6.2). Open the IDE and click to the Sketch menu and then Include Library > Manage Libraries.
Then the Library Manager will open and you will find a list of libraries that are already installed or ready for installation. In order to install The IoT Guru integration, search for “The IoT Guru integration“, scroll the list to find it and click on it.
Finally click on install and wait for the IDE to install The IoT Guru integration. Downloading may take time depending on your connection speed. Once it has finished, an Installed tag should appear next to the The IoT Guru integration library. You can close the Library Manager.
You can now find The IoT Guru integration available in the Sketch > Include Library menu.
We included some examples to our library, so that you can choose various examples to integrate your devices with our services, for example the basic device connection:
This high-quality camera is equipped with an IMX477 12.3MP high quality camera module which adopts the IMX477R sensor. It supports CS-mount lenses by default, but however, a C-CS adapter is included in order to use C mount lenses as well with this camera. It is compatible with Raspberry Pi Compute Module 3, 3 Lite, 3+, 3+ Lite, and NVIDIA Jetson Nano. This offers a higher resolution (12.3MP) and higher sensitivity (nearly 50% greater area per pixel for improved low-light performance) than the traditional 8MP IMX219 cameras.
Sony IMX477 sensor with 12.3MP for high resolution
Greater pixel area for improved low-light performance
Back-illuminated sensor architecture for improved sensitivity
Seeeduino XIAO is the smallest Arduino compatible board in Seeeduino Family. It is an Arduino microcontroller that is embedded with the SAMD21 microchip. The interfaces of Seeeduino XIAO is rich enough in such a tiny Dev. Board as well.