EdgeReady MCU Based Solution for Alexa for IOT

MCU-VOICE-CONTROL-AVS
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NXP EdgeReady MCU-based solution for Amazon's Alexa Voice Service (AVS) integration for AWS IoT Core (aka Alexa for IoT, or AFI), leverages the i.MX RT crossover MCU, enabling developers to quickly and easily add Alexa voice assistant capabilities to their products. Part of the EdgeVerse edge computing platform, This i.MX RT106A based turnkey solution consists of a hardware reference design integrated with Amazon qualified software, built on Amazon Common Software (ACS) and FreeRTOS for easy integration with AVS and AWS IoT. Out-of-the-box the solution development kit, SLN-ALEXA-IOT, delivers an experience similar to an Amazon Echo™ speaker, and is easily connected to the user’s Wi-Fi network and Alexa account using Amazon’s Frustration Free Setup (FFS).

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Product Details

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Block Diagram

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i.MX RT Hardware

i.MX RT106A Reference Design Block Diagram

i.MX RT Software

i.MX RT106A Voice Control Software Block Diagram
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Supported Devices

Processors and Microcontrollers

i.MX RT Crossover MCUs

  • i.MX-RT1060: i.MX RT1060: Crossover MCU with Arm® Cortex®-M7

Features

Qualifications

  • Amazon Alexa Voice Service (AVS) qualified
  • Amazon Frustration Free Setup (FFS) qualified

Versatility

  • No voice or audio expertise required, and built on FreeRTOS and Amazon Common Software (ACS) for easy integration with AVS and AWS IoT,
  • Supports up to three low cost MEMS microphones for 360° far field voice (only two microphones needed for 180° applications)

ADC/DAC Conversion

  • On chip MQS DAC for low cost audio playback with inexpensive analog amplifier

Protocols

  • AVS Integration for AWS IOT Core (AFI)
  • MQTT, lwIP, mBedTLS

Single Power Supply

  • 3.3 V supply

Low-dropout Regulation

  • DC-to-DC and LDO

Temperature Control

  • Temp monitor

External

  • 16 MB QSPI Flash (to support over the air updates)

Internal

  • 1 MB on-chip RAM

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SLN-ALEXA-IOT-Image

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    • Inventory: 12
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Documentation

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Software

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Note: For better experience, software downloads are recommended on desktop.

Training

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