awslabs / aws-iot-core-integration-with-nvidia-deepstream

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AWS IoT Core Integration with NVIDIA DeepStream

This project implements protocol adaptor between NVIDIA DeepStream SDK and AWS (edge to cloud messaging). The adaptor implements the API for client applications to publish inference results or metadata using MQTT messages to AWS IoT Core.

Pre-requisites

For the convenience of this installation, we can create an environment variable of the path where you DeepStream SDK is installed. Please replace to the path of your DeepStream SDK on your Jetson device. (For DeepStream 5.0, the default installation path is "/opt/nvidia/deepstream/deepstream-5.0/".)

export DEEPSTREAM_SDK_PATH=<DeepStream SDK PATH>

Installation Guide:

Step 1: Download AWS DeepStream adaptor

In your Jetson device, navigate to Downloads folder, then download or clone the AWS managed GitHub repo. Copy the aws_protocol_adaptor sub-folder to ${DEEPSTREAM_SDK_PATH}/sources/libs.

cd ~/Downloads
git clone https://github.com/awslabs/aws-iot-core-integration-with-nvidia-deepstream.git
cd aws-iot-core-integration-with-nvidia-deepstream
cp -r aws_protocol_adaptor ${DEEPSTREAM_SDK_PATH}/sources/libs

[Optional] Step 2: Manually build the shared library (You can skip this step if you want to use the .so file that we built for you.)

he shared library (.so file) is built and checked in the git repo you cloned in Step 1 in the aws_protocol_adaptor/device_client directory. If you want to build and customize your shared library, you can follow step 2 to compile with customized features such as optimized buffer size for incoming or outgoing MQTT messages, or TLS connection timeout values.

If cloned or downloaded successfully, aws_protocol_adaptor should appear in your current path. Next, we need to create an empty directory for AWS IoT device SDK library. We also need to clone the AWS IoT device SDK in Embedded-C version 3 into this empty directory we created. (Please note that we are aware that AWS IoT Embedded SDK Version 4 does not currently work with this project. It is in our roadmap to support this latest version 4 SDK in the near future.)

mkdir ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/aws-iot-sdk
cd ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/aws-iot-sdk
git clone --branch v3.1.1 https://github.com/aws/aws-iot-device-sdk-embedded-C.git

This AWS IoT device SDK has an external dependency on Mbed TLS, so navigate to aws-iot-sdk/external_libs/. And clone the existing Mbed TLS repo in this folder:

cd ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/aws-iot-sdk/external_libs/mbedTLS
git clone https://github.com/ARMmbed/mbedtls.git

Navigate to device_client folder, and compile the shared library:

cd ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client
make clean
make

If you inspect this current folder, you should see the libnvds_aws_proto.so file just updated.

Step 3: Provision DeepStream App with AWS IoT credentials

Navigate to AWS web console, and go to IoT Core service. On the left-side menu, click on SecurePolicies. And on the right upper corner, click on Create. A window would appear to help you create a policy for your thing you are about to create for DeepStream Application. You can also do this with AWS CLI. Please refer to AWS IoT Policy Elements for list of actions in AWS IoT to allow or deny.

After creating the policy, you can then create a thing for DeepStream Application. You can do this on AWS console by going to the left-side AWS IoT service page, click on Manage->Things. And on the right upper corner, click on Create. This would start the process of creating a thing on AWS IoT. You can also do this with AWS CLI. Please note down the thing name you have used to create this thing, you will later need it.

If you are using AWS console, after creating the thing, a new page would appear with download links for the certificates we just generated for this thing, download all of them. For root certificate, a link would redirect you to a root certificate download page. You can download Amazon Root CA1. And you can click on the Activate button on this page to activate the set of certificates that you just downloaded.

Then click on Attach Policy, and choose the policy named ds_app_policy you just created.

Step 4: Transfer certificates to Jetson device

Navigate to the path of your downloaded certs. You should see four files in the following naming format:

XXX-certificate.pem.crt
XXX-private.pem.key
XXX-public.pem.key
AmazonRootCA1.pem

You can change them to:

certificatePem.cert.pem
privateKey.private.key
publicKey.public.key
root.ca.pem

You can then make a cert folder on your Jetson device, and transfer these downloaded certificates and keys to your Jetson device. In this demo, we are going to put these certificates in the following directory.

mkdir ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client/certs
mv <4 CERTS FILES> ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client/certs

On your Jetson device, navigate to:

cd ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client/

Edit cfg_aws.txt:

Step 5: Run Deepstream App

We are going to use the test apps developed by NVIDIA to verify our adaptor setup. We are going to run tests with both test4 and test5 in NVIDIA DeepStream SDK sample app folder. The deepstream-test4 can be used to demonstrate adding custom objects as NVDS_EVENT_MSG_META user metadata with buffers for generating a custom payload to be published to AWS IoT Core. The deepstream-test5 can demonstrate how to use "nvmsgconv" and "nvmsgbroker" plugins in the pipeline, create NVDS_META_EVENT_MSG type of meta, and upload to AWS IoT Core. Both apps can help verify the installation and functionalities of this message broker.

Install dependency on your Jetson

Install libgstrtspserver-1.0-dev

sudo apt-get install libgstrtspserver-1.0-dev

Test App 4

Please first navigate to test4 in your DeepStream SDK, and make the app:

cd ${DEEPSTREAM_SDK_PATH}/sources/apps/sample_apps/deepstream-test4
make

Then, you can use the following command to run test4.

./deepstream-test4-app -i ../../../../samples/streams/sample_720p.h264 -p ../../../libs/aws_protocol_adaptor/device_client/libnvds_aws_proto.so --conn-str=hello -c ../../../libs/aws_protocol_adaptor/device_client/cfg_aws.txt -t test --no-display

Now navigate to AWS IoT console, and on the menu bar on the left, click on test, type in test (or # to receive messages on all topics) in the subscription topic box, and click on Subscribe to topic, you should see MQTT messages start to show up on this console after app successfully runs: Image of success

Test App 5

Please navigate to test5 in your DeepStream SDK, and make the app. Please note you need a display connected for this test app.

cd ${DEEPSTREAM_SDK_PATH}/sources/apps/sample_apps/deepstream-test5
make

In order to run deepstream-test5, you also need to modify your configuration file to point at the shared library.

cp configs/test5_config_file_src_infer.txt configs/test5_config_file_src_infer_aws.txt
vim configs/test5_config_file_src_infer_aws.txt

You can then, modify msg-broker-proto-lib under your message broker sink (sink1), to point to: ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client/libnvds_aws_proto.so. And also modify msg-broker-config under the same sink to point to: ${DEEPSTREAM_SDK_PATH}/sources/libs/aws_protocol_adaptor/device_client/cfg_aws.txt Next, you need to modify the topic to a topic name that you choose, and modify the first sink to a fake sink. Then, you can use the following command to run test5:

./deepstream-test5-app -c configs/test5_config_file_src_infer_aws.txt

Now navigate to AWS IoT console, and on the menu bar on the left, click on test, type in test (or # to receive messages on all topics) in the subscription topic box, and click on Subscribe to topic, you should see MQTT messages start to show up on this console after app successfully runs.

Processing IoT messages with AWS IoT rule

Once you see messages coming into AWS IoT Core, there are a lot of options to further process them or store them on AWS cloud. One simple example would be to push these messages, using AWS IoT Rules, to a customized AWS Lambda function, which parses the messages and puts them in Amazon DynamoDB. You may find the following documents helpful in setting up this IoT rule to storage pipeline:

The following documents may further assist you building a more production-ready data pipeline:

Compatible with AWS IoT Greengrass

This AWS DeepStream adaptor also supports connecting to AWS IoT Greengrass. You can modify in cfg_aws.txt to your Greengrass Endpoint/IP address.

There are several options to find out Greengrass Endpoint/IP address. If you know the IP address of your Greengrass device or run “ifconfig” on your Greengrass device to find it out, you can directly put that as . AWS IoT Greengrass also provides a Discovery API, enabling devices to retrieve information required to connect to an AWS IoT Greengrass core that is in the same Greengrass group as the device.

For further information on enabling your device to connect to AWS IoT Greengrass, please follow module 4 in AWS IoT Greengrass developer guide.

Re-compiling Guide:

You can always change this library to suit your own need. Please make the change the code and follow "Step 2: Manually build the shared library" section to make a new shared library for DeepStream. Some additional message properties like buffer size, can be set in aws_iot_config.h. If you want to change any of these settings, you will have to compile your own .so file.

For we used QoS 0 for all the send functions. However, you can adjust to QoS 1 in message broker source code: aws_nvmsgbroker.c.

To adjust the level of IOT logging, please go to Makefile and comment or un-comment the following lines.

LOG_FLAGS += -DENABLE_IOT_DEBUG
LOG_FLAGS += -DENABLE_IOT_INFO
LOG_FLAGS += -DENABLE_IOT_WARN
LOG_FLAGS += -DENABLE_IOT_ERROR

License

This project is licensed under the Apache-2.0 License.