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AmebaPro Introduction

AmebaPro is one of the Ameba IoT Family System On Chip which integrates the following features

  • Wi-Fi 802.11ac/n

  • H.264

  • Image Signal Processing/ISP

  • Audio Codec

  • SD Storage

AmebaPro is based on the ARM cortex v8m up to 300MHz with 32/64MB LPDDR. The high performance capability enables the comparatively complicated video and vision application, while still be a best choice for battery-based product. The highly integrated solution makes it possible to have a smaller form factor design, which is more cost effective and has rich potentiality.

It has FreeRTOS running on it, and provides standard BSD socket and Posix interface for easier open sources integration. The simplicity of RTOS architecture achieves fast boot capability, which is a big benefit from both key product feature, and power consumption point of view.

By integration of image sensing and communication technology, AmebaPro transmits the video or picture to the cloud, which then bridges the back-end AI service for computer vision application. It realizes a lightweight IoT device to have intelligent vision capability.

AmebaPro with KVS WebRTC and Producer

This demonstrates how to use KVS Producer and WebRTC on AmebaPro. test image size

AmebaPro_RTOS_Amazon_Eco_System

Amazon FreeRTOS-LTS libraries are supported on AmebaPro now, it can be used to communicate with AWS IoT core easily! Version 202012.00

Brief Introduction to Amazon KVS and FreeRTOS-LTS

📘 Amazon Kinesis Video Streams
  include two main services, which are Producer and WebRTC test image size

📘 KVS Producer
  stream live video from devices to the AWS Cloud, or build applications for batch-oriented video analytics. test image size

📘 KVS WebRTC
  enable real-time communication (RTC) across browsers and mobile applications via simple APIs. test image size

📘 FreeRTOS-LTS Libraries
  provides feature stability, and security patches and critical bug fixes for two years from release date. test image size

Applications on AmebaPro

💡 AI Face Detection

  AmebaPro(Producer) + Rekognition(AWS AI) = video cloud storage and content analytics ☁️

test image size 1. Stream live video from AmebaPro to KVS

2. AI face detection by using AWS Rekognition API

  👉  

💡 Real-time communucation

  AmebaPro(WebRTC master) + Viewer(WebRTC Client) = real-time communication, 1-way video & 2-way audio

test image size 1. AmebaPro start a signaling channel, as a master

2. Browser run as a viewer (client)

3. Start a P2P connection

  👉  

💡 Object Detection

  AmebaPro(image uploader) + Rekognition(AWS AI) = object detection and classification ☁️

test image size 1. Take a snapshot by camera sensor

2. Upload image from AmebaPro to S3

3. Trigger Lambda function to do object detection

  👉  

Notes: Based on FreeRTOS-v202012-LTS framework

💡 FreeRTOS-LTS-v202012.00 Libraries

  AmebaPro can connect to AWS IoT with the long term support libraries maintained by Amazon.
  FreeRTOS demos: coreHTTP, coreMQTT, Over-the-air updates(OTA), AWS IoT Device Shadow...

Demo code

✏️ KVS WebRTC    lib_amazon/amazon-kinesis-video-streams-webrtc-sdk-c-for-freertos/main_amebapro

✏️ KVS Producer    lib_amazon/amazon-kinesis-video-streams-producer-embedded-c/samples/kvs-amebapro

✏️ S3 file upload    project/component/common/application/amazon/JPEG_snapshot_s3_upload_example

✏️ FreeRTOS-LTS    lib_amazon/amazon-freertos-202012.00/demos

IDE/toolchain Requirement

🔨 IAR Embedded Workbench - IAR Systems
  Please use IAR version 8.3

🔨 GCC toolchain
  Linux: asdk-6.4.1-linux-newlib-build-3026-x86_64
  Cygwin: asdk-6.4.1-cygwin-newlib-build-2778-i686

Clone Project

To check out this repository:

git clone --recurse-submodules https://github.com/ambiot/ambpro1_sdk.git

If you already have a checkout, run the following command to sync submodules recursively:

git submodule update --init --recursive

If there is GCC makefile error like: "No rule to make target …", it may mean that some codes have not been downloaded correctly.
Please run the above command again to download the missing codes.

If there is compile error with shell script in "component/soc/realtek/8195b/misc/gcc_utility/", you may need to run following command

dos2unix component/soc/realtek/8195b/misc/gcc_utility/*