Technical Documents
Specifications
Brand
CoralProduct Type
Microcontroller Development Tool
Kit Classification
Microcontroller Board
Kit Name
Dev Board Micro
Technology
ARM Cortex
Device Core
ARM Cortex M7
Processor Family Name
ARM
Processor Part Number
i.MX RT1176
Processor Type
Microcontroller
Standards/Approvals
No
Country of Origin
China
Product Details
The Coral Dev Board Micro is a microcontroller board that benefits from a built-in camera,microphone, and Coral Edge TPU, allowing you to quickly prototype and deploy low-power embedded systems with on-device ML inferencing.
By combining the Cortex M4 and M7 processors with the Coral Edge TPU on this board, you can design systems that cascade from extreme low-power ML inferencing to more complex—yet still power-efficient—ML inferencing.
You can also expand the hardware with custom add-on boards using the high-density board-to-board connectors. The Edge TPU is a small ASIC designed by Google that accelerates tensor flow lite models in a power efficient manner. One Edge TPU is capable of performing 4 trillion operations per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection.
Stock information temporarily unavailable.
€ 80.52
€ 80.52 Each (Exc. VAT)
1
€ 80.52
€ 80.52 Each (Exc. VAT)
Stock information temporarily unavailable.
1
Technical Documents
Specifications
Brand
CoralProduct Type
Microcontroller Development Tool
Kit Classification
Microcontroller Board
Kit Name
Dev Board Micro
Technology
ARM Cortex
Device Core
ARM Cortex M7
Processor Family Name
ARM
Processor Part Number
i.MX RT1176
Processor Type
Microcontroller
Standards/Approvals
No
Country of Origin
China
Product Details
The Coral Dev Board Micro is a microcontroller board that benefits from a built-in camera,microphone, and Coral Edge TPU, allowing you to quickly prototype and deploy low-power embedded systems with on-device ML inferencing.
By combining the Cortex M4 and M7 processors with the Coral Edge TPU on this board, you can design systems that cascade from extreme low-power ML inferencing to more complex—yet still power-efficient—ML inferencing.
You can also expand the hardware with custom add-on boards using the high-density board-to-board connectors. The Edge TPU is a small ASIC designed by Google that accelerates tensor flow lite models in a power efficient manner. One Edge TPU is capable of performing 4 trillion operations per second. This on-device ML processing reduces latency, increases data privacy, and removes the need for a constant internet connection.
