Azure Digital Twins End-To-End Sample

Contents

• Flow
• Semiconductor Film Thickness Measurement System - FilmCheck AS300
• Edge Computing Hardware
• Azure Cloud service used
• Development Environment
• Prerequisites
• Digital Twins Definition Language
• Data transmission format
• The path of the Log & Report & Image in Azure Blob
• The file structure in the Github repository
• Step-by-step Guide
  • 0. If the prerequisite for the environment is to use Azure Ubuntu VM
  • 1. Preparing the operating environment
  • 2. Set Environment Variable
  • 3. Create a resource group
  • 4. Deploying Azure Digital Twin
    • Create an Azure Digital Twin
    • Get User Principal Name
    • Set Role Assignment
    • Check Role Assignment
    • Upload DTDL Model
    • Create the Twins
    • Initial Property
    • Create a Relationship
    • List Relationship
    • Check
  • 5. Create Azure IoT Hub and Create IoT Device
  • 6. Build Azure 3D Scenes Studio
  • 7. Setting up notifications to be sent through Microsoft Teams
  • 8. Database environment setup and configuration
  • 9. Deploy the Azure Container Apps
    • Upgrade the Azure CLI
    • Create an Azure Container Registry
    • List the container registries under the current subscription
    • Log in to the Azure Container Registry
    • Create a Docker Image
    • Check Azure container registry from Browser
    • Create a Container Apps Environments
    • Get default Domain
    • Deploy your image to Azure Container App
  • 10. Deploying the Frontend to Azure Static Web Apps
  • 11. Launching the program on the Edge
  • 12. Launch the program for FilmCheck AS300
  • 13. Confirming the results from Azure Digital Twins 3D Scenes Studio
  • 14. Confirming the results from the frontend
  • 15. Confirming the results from the Microsoft HoloLens
  • 16. Analysis and Learning of Film Thickness Data
• Reference
• Contributor
• License

Flow

This project contains a sample for working with Azure Digital Twins：

• A building scenario sample written in Vue, Node.js, and Python. The sample can be used to set up and a full end-to-end scenario with Azure Digital Twins.
• The designed flow and architecture is showed as following：
  • Upload the corresponding status and measurement results of the Semiconductor Film Thickness Measurement System (FilmCheck AS300) in DTDL format to Azure Digital Twins.
  • Sending the status and measurement results of the Semiconductor Film Thickness Measurement System (FilmCheck AS300) to the edge for analysis and serialization, and then transmitting to Azure IoT Hub.
  • After analyzing the relevant data received from Azure IoT Hub, the program deployed in the Azure Container App writes it into the corresponding property in Azure Digital Twin.
  • Retrieve the corresponding properties from Azure Digital Twins and display them in Azure 3D Scenes Studio.
  • Use Microsoft HoloLens to understand the current status and measurement results of the Semiconductor Film Thickness Measurement System (FilmCheck AS300) through the dashboard deployed in Azure Static Web App.
  • When an error occurs in the Semiconductor Film Thickness Measurement System (FilmCheck AS300), send an alert message to the administrator group in real-time via Microsoft Teams.
  • Upload the logs and reports received from the Semiconductor Film Thickness Measurement System (FilmCheck AS300) on Edge to Azure Blob. When Azure Blob receives the upload event of the report, trigger the Azure Machine Learning pipeline to perform data analysis and generate results, then upload them to Azure Blob and Job Metrics/Images.
  • Keyword：
    • Azure IoT Hub, Docker, Azure Container Registry, Azure Container Apps, Azure Digital Twins, Digital Twins Definition Language (DTDL), Azure 3D Scenes Studio, Azure Digital Twins Explorer, Azure App Service, Microsoft HoloLens, Creating a 3D model of a physical object, Babylon.js, Azure Machine Learning, Azure Static Web App, Vue, Azure storage account, Azure Database for PostgreSQL, GitHub, Azure Active Directory and Microsoft Teams.

Semiconductor Film Thickness Measurement System - FilmCheck AS300

Spectral reflectometer (SR) is a method of characterizing unknown properties of a sample by measuring the reflection of electromagnetic radiation. The reflected light is collected onto the spectrometer and transfer into spectrum signals. After the theoretical analysis and signature fitting, the parameters of the sample can be obtained. In our system, it can measure the parameters of film thickness, (n, k) value, and TSV (through silicon via) depth (option).

• Features
  • Extra film thickness range up to 150 µm
  • Fast alignment with high reliability R - Θ stage
  • Precise measurement location for patterned film
  • Generate map recipe in seconds
  • Double check measurement location by preview color camera
  • Auto focusing for precise measurement
• Specifications
  • Oxide, Nitride, PR, PI film on Si, GaAs, glass, metals substrate
  • Excellent for patterned film with auto mapping
  • Mapping size up to 300 mm wafer
  • Absolute reflectivity measurements
  • Film thickness range: 200 Å ~ 150 µm
  • Repeatability: <br 10 Å @ 5000 Å Oxide on Si substrate
  • Measurement Spot Size: φ40 µm (available others)
  • Wafer size compatibility: 4”, 6”, 8”, 12”
  • SEMI S2 compliance
• Infomation

Edge Computing Hardware

• NVIDIA® Jetson AGX Xavier™

Azure Cloud service used

• Azure IoT Hub
• Azure Event Hub
• Azure Active Directory
• Azure Digital Twins
• Azure Digital Twins Explorer
• 3D Scenes Studio for Azure Digital Twins
• Azure Container Registry
• Azure Container Apps
• Azure Machine Learning Studio
• Azure Static Web Apps
• Azure Storage Account
• Azure Database for PostgreSQL

Development Environment

Application	Development Environment - Hardware / OS	Language
Edge	NVIDIA Jetson AGX Xavier	Python 3.6
Cloud	MacBook Pro M1 Max (macOS: Ventura 13.0.1) You can also use an Azure Ubuntu VM to perform the following operations.	Node v18.13.0 (LTS)

Prerequisites

• Sign in to the Azure portal
• Install the Azure CLI
• Sign in with Azure CLI
• Install the Visual Studio Code
• Install the Docker CLI
• Install the pgAdmin
• Sign in to GitHub
• Install Node.js
• Install Git and Sign in to GitHub

Digital Twins Definition Language

The DTDL model is defined as following 2 sections:

• Lab

{
    "@id": "dtmi:itri:Lab;1",
    "@type": "Interface",
    "@context": "dtmi:dtdl:context;2",
    "displayName": "Lab",
    "contents": [
     {
      "@type": "Relationship",
      "name": "contains",
      "properties": [
       {
        "@type": "Property",
        "name": "targetModel",
        "schema": "string"
       }
      ],
      "target": "dtmi:itri:cms:filmcheck;1"
     }
    ]
   }

• Semiconductor Film Thickness Measurement System (FilmCheck AS300)

Type Error	Machine Status	Color	Annotation
-1	Shutdown	Default Color	The program for FilmCheck AS300 has been closed.
0	Idle	Green	The program for FilmCheck AS300 has been opened.
1	inOperation	Orange	The program for FilmCheck AS300 is currently performing wafer inspection.
2	Error	Red	An error occurred during wafer inspection in the program for FilmCheck AS300.

{
  "@context": [
    "dtmi:dtdl:context;2"
  ],
  "@id": "dtmi:itri:cms:filmcheck;1",
  "@type": "Interface",
  "displayName": "FilmCheck Device",
  "description": "FilmCheck Device",
  "contents": [
    {
      "@type": "Property",
      "name": "statusDate",
      "displayName": "status date",
      "description": "status date",
      "schema": "string"
    },
    {
      "@type": "Property",
      "name": "statusTime",
      "displayName": "status time",
      "description": "status time",
      "schema": "string"
    },
    {
      "@type": "Property",
      "name": "typeError",
      "displayName": "status type",
      "description": "status type",
      "schema": "integer"
    },
    {
      "@type": "Property",
      "name": "statusMessage",
      "displayName": "status message",
      "description": "status message",
      "schema": "string"
    },
    {
      "@type": "Property",
      "name": "statisticsDate",
      "displayName": "statistics date",
      "description": "statistics date",
      "schema": "string"
    },
    {
      "@type": "Property",
      "name": "statisticsTime",
      "displayName": "statistics time",
      "description": "statistics time",
      "schema": "string"
    },
    {
      "@type": "Property",
      "name": "statisticsStandardDeviation",
      "displayName": "statistics standard deviation",
      "description": "statistics standard deviation",
      "schema": "double"
    },
    {
      "@type": "Property",
      "name": "statisticsAverage",
      "displayName": "statistics average",
      "description": "statistics average",
      "schema": "double"
    },
    {
      "@type": "Property",
      "name": "statisticsUniformity",
      "displayName": "statistics uniformity",
      "description": "statistics uniformity",
      "schema": "double"
    },
    {
      "@type": "Property",
      "name": "statisticsMax",
      "displayName": "statistics max",
      "description": "statistics max",
      "schema": "double"
    },
    {
      "@type": "Property",
      "name": "statisticsMin",
      "displayName": "statistics min",
      "description": "statistics min",
      "schema": "double"
    },
    {
      "@type": "Property",
      "name": "statisticsMaxMin",
      "displayName": "statistics max min",
      "description": "statistics max min",
      "schema": "double"
    }
  ]
}

Data transmission format

• Transferring data from the Semiconductor Film Thickness Measurement System to the Edge

  • Shutdown

    {
      "date": "2023/02/23",
      "time": "13:43:34",
      "message": "Shutdown: The program is preparing to close."
    }

  • Idle

    {
      "date": "2023/02/23",
      "time": "13:43:34",
      "message": "Idle: The program is already open but wafer inspection has not yet started."
    }

  • inOperation

    {
      "date": "2023/02/23",
      "time": "13:43:34",
      "message": "inOperation: The wafer inspection is in progress."
    }

  • Error

    {
      "date": "2023/02/23",
      "time": "13:43:34",
      "message": "Error: OpenSensor() : Sensor usb device list failed or no sensor present : 0x1"
    }

• Transferring data from the Edge to Azure IoT Hub

Type Error	Machine Status (type)	Color	Annotation
-1	Shutdown	Default Color	The program for FilmCheck AS300 has been closed.
0	Idle	Green	The program for FilmCheck AS300 has been opened.
1	inOperation	Orange	The program for FilmCheck AS300 is currently performing wafer inspection.
2	Error	Red	An error occurred during wafer inspection in the program for FilmCheck AS300.

{
	"status": {
		"date": "2023/01/11",
		"time": "09:18:50",
		"type": "Error",
		"message": "-999 Failed to load the configuration file."
	},
	"statistics": {
		"date": "2023/01/11",
		"time": "09:18:50",
		"standardDeviation": 769.93,
		"average": 54954.8,
		"uniformity": 98.599,
		"max": 54954.8,
		"min": 54954.8,
		"maxMin": 54954.8,
		"fileName": "20230220-011029.csv",
	}
}

The path of the Log & Report & Image in Azure Blob

Type	Name	Azure Blob
Log	L20230218.log	adt3dstorageaccount/adt/Log
Report	20230220-011029.csv	adt3dstorageaccount/adt/Report
Image	20230220-011029.png	adt3dstorageaccount/adt/Image

The file structure in the Github repository

├── 3D-Scenes
│   └── semi-v1.glb
├── AzureContainerApp
│   ├── Blob_Trigger
│   │   ├── config
│   │   │   └── config.json
│   │   ├── docker-manifests
│   │   │   └── Dockerfile
│   │   ├── index.js
│   │   ├── migrations
│   │   │   └── 20230219235350-create-log.js
│   │   ├── models
│   │   │   ├── index.js
│   │   │   └── log.js
│   │   ├── package-lock.json
│   │   ├── package.json
│   │   └── tokenService.js
│   ├── DB_Ops
│   │   ├── config
│   │   │   └── config.json
│   │   ├── docker-manifests
│   │   │   └── Dockerfile
│   │   ├── index.js
│   │   ├── migrations
│   │   │   ├── 20230219235350-create-log.js
│   │   │   ├── 20230220012714-create-report.js
│   │   │   └── 20230309235001-create-status.js
│   │   ├── models
│   │   │   ├── index.js
│   │   │   ├── log.js
│   │   │   ├── report.js
│   │   │   └── status.js
│   │   ├── package-lock.json
│   │   └── package.json
│   ├── IoTHub_To_ADT_Notify
│   │   ├── adtService.js
│   │   ├── config
│   │   │   └── config.json
│   │   ├── docker-manifests
│   │   │   └── Dockerfile
│   │   ├── index.js
│   │   ├── migrations
│   │   │   ├── 20230220012714-create-report.js
│   │   │   └── 20230309234114-create-status.js
│   │   ├── models
│   │   │   ├── index.js
│   │   │   ├── report.js
│   │   │   └── status.js
│   │   ├── package-lock.json
│   │   └── package.json
│   └── Query_ADT
│       ├── adtService.js
│       ├── docker-manifests
│       │   └── Dockerfile
│       ├── index.js
│       ├── package-lock.json
│       └── package.json
├── AzureML
│   ├── pipeline-python
│   │   └── go.py
│   └── run_pipeline.ipynb
├── DM
│   └── FilmChek_AS300.png
├── DTDL
│   ├── 3D-FilmCheck-v1.json
│   └── Lab.json
├── Edge
│   ├── Datas
│   │   ├── L20230301-Error.log
│   │   ├── L20230301-Idle.log
│   │   ├── L20230301-Shutdown.log
│   │   ├── L20230301-inOperation.log
│   │   └── L20230301.log
│   ├── Excel
│   │   └── 20230305-144311.xlsx
│   ├── Log
│   ├── Report
│   │   └── 20230313-140020.csv
│   ├── edge.py
│   ├── publisher-test
│   │   ├── pubLog.py
│   │   └── pubReport.py
│   ├── requirements.txt
│   └── uploadFileToBlob
│       ├── Log
│       │   └── L20230301.log
│       ├── Report
│       │   └── 20230313-140020.csv
│       ├── app.py
│       └── requirements.txt
├── Frontend
│   ├── README.md
│   ├── babel.config.js
│   ├── jsconfig.json
│   ├── package-lock.json
│   ├── package.json
│   ├── public
│   │   ├── assets
│   │   │   └── semi-v1.glb
│   │   ├── favicon.ico
│   │   ├── index.html
│   │   └── itri-64.ico
│   ├── src
│   │   ├── App.vue
│   │   ├── assets
│   │   │   └── logo.png
│   │   ├── components
│   │   │   ├── InfoModal.vue
│   │   │   └── SpinnerModal.vue
│   │   ├── main.js
│   │   ├── router
│   │   │   └── index.js
│   │   ├── scenes
│   │   │   └── Scene.js
│   │   ├── store
│   │   │   └── index.js
│   │   └── views
│   │       └── IndoorView.vue
│   └── vue.config.js
├── README.md
└── Script
    └── install-docker.sh

Step-by-step Guide

0. If the prerequisite for the environment is to use Azure Ubuntu VM

• Log in to Azure Ubuntu VM

  ssh Account@Azure-Ubuntu-VM-IP
  

• Download the zip file of the source code

  git clone https://github.com/ArcherHuang/Azure-Digital-Twins-End-To-End-Sample.git
  

  

• Insatll Docker Engine

  • Switch the working directory

    cd ./Azure-Digital-Twins-End-To-End-Sample/Script
    

    

  • Change file permissions

    chmod 777 install-docker.sh
    

    

  • Install Docker

    sudo ./install-docker.sh
    

    

• Install Buildx

  sudo apt-get install qemu qemu-user-static qemu-user
  
  mkdir -p ~/.docker/cli-plugins
  
  sudo docker version --format '{{.Server.Experimental}}' | grep -q 'true' && DOCKER_BUILDKIT=1 || DOCKER_BUILDKIT=0
  
  curl -SL https://github.com/docker/buildx/releases/download/v0.6.1/buildx-v0.6.1.linux-amd64 -o ~/.docker/cli-plugins/docker-buildx
  
  chmod a+x ~/.docker/cli-plugins/docker-buildx
  
  docker buildx install
  
  docker buildx version
  

  

• Install Azure CLI

  curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
  
  az --version
  

  

• Sign in to Azure via AZ CLI

  az login
  

• Get subscription ID

  az account subscription list
  

  

• Switch to the subscription to be used

  az account set --subscription "SUBSCRIPTION-ID"
  

• Install Node.js

  curl -s https://deb.nodesource.com/setup_16.x | sudo bash
  
  sudo apt install nodejs -y
  
  node -v
  

  

1. Preparing the operating environment

• Commands for macOS environment

  • Download the zip file of the source code

    • Click the Code button > Click the Download ZIP button

  • Unzip the zip file and Switch the working directory to the folder that has been extracted

    cd ./Azure-Digital-Twins-End-To-End-Sample-main
    

• Please remember to log in to Azure using Azure CLI.

2. Set Environment Variable

• Commands for macOS and Ubuntu environment

export RESOURCE_GROUP="adt-3d-rg"
export REGION="japaneast"
export ADT_NAME="adt-3d"
export BLOB_NAME="adt3dstorageaccount"
export BLOB_CONTAINER_NAME="adt"
export ACR_NAME="containerforacr"
export ACA_NAME_HUB="adt3dhub"
export ACA_NAME_QUERY="adt3dquery"
export ACA_NAME_BLOB="blobtrigger"
export ACA_NAME_DB_Ops="dbops"
export ACA_ENVIRONMENT_HUB="env-region-containerapps-hub"
export ACA_ENVIRONMENT_QUERY="env-region-containerapps-query"
export ACA_ENVIRONMENT_BLOB="env-region-containerapps-blob"
export ACA_ENVIRONMENT_DB_OPS="env-region-containerapps-db-ops"
export IOT_HUB_NAME="adt-3d"
export IOT_DEVICE_NAME="FilmCheck01"
export IOT_HUB_CONSUMER_GROUP_CONTAINER_APP="containerapp"
export IOT_HUB_CONSUMER_GROUP_STATIC_WEB_APP="forStaticWeb"
export DB_PG_NAME="semiconductor"
export DB_SKU="GP_Gen5_2"
export DB_USER_NAME="azureuser"
export DB_USER_PASSWORD="Pa~w@0rD"

echo $RESOURCE_GROUP
echo $REGION
echo $ADT_NAME
echo $BLOB_NAME
echo $BLOB_CONTAINER_NAME
echo $ACA_NAME_HUB
echo $ACA_NAME_QUERY
echo $ACA_NAME_BLOB
echo $ACA_NAME_DB_Ops
echo $ACA_ENVIRONMENT_HUB
echo $ACA_ENVIRONMENT_QUERY
echo $ACA_ENVIRONMENT_BLOB
echo $ACA_ENVIRONMENT_DB_OPS
echo $IOT_HUB_NAME
echo $IOT_DEVICE_NAME
echo $IOT_HUB_CONSUMER_GROUP_CONTAINER_APP
echo $IOT_HUB_CONSUMER_GROUP_STATIC_WEB_APP
echo $DB_PG_NAME
echo $DB_SKU
echo $DB_USER_NAME
echo $DB_USER_PASSWORD

3. Create a resource group

• Commands for macOS and Ubuntu environment

  az group create --name $RESOURCE_GROUP --location $REGION
  

  

4. Deploying Azure Digital Twin

• Create an Azure Digital Twin

  • Commands for macOS and Ubuntu environment

    az dt create -n $ADT_NAME -g $RESOURCE_GROUP -l $REGION
    

    

• Get Azure Digital Twin Host URL

  • Commands for macOS and Ubuntu environment

  export ADT_Host_Name=`az dt show --dt-name $ADT_NAME --resource-group $RESOURCE_GROUP --query hostName`
  
  echo $ADT_Host_Name
  

  

• Get User Principal Name

az ad user list

• Set parameter

  • Commands for macOS and Ubuntu environment

    export USER_PRINCIPAL_NAME="Change it to the userPrincipalName obtained in the previous step."
    
    echo $USER_PRINCIPAL_NAME
    

• Set Role Assignment

  • Commands for macOS and Ubuntu environment

    az dt role-assignment create -n $ADT_NAME --assignee $USER_PRINCIPAL_NAME --role "Azure Digital Twins Data Owner" -g $RESOURCE_GROUP
    

    

• Check Role Assignment

  • Commands for macOS and Ubuntu environment

    az dt role-assignment list -n $ADT_NAME -g $RESOURCE_GROUP
    

    

• Upload DTDL Model

  • Commands for macOS and Ubuntu environment

    az dt model create -n $ADT_NAME --from-directory ./DTDL -g $RESOURCE_GROUP
    

    

• Create the Twins

  • Lab

    • Commands for macOS and Ubuntu environment

      az dt twin create -n $ADT_NAME --dtmi "dtmi:itri:Lab;1" --twin-id DistCtr -g $RESOURCE_GROUP
      

      

  • Semiconductor Film Thickness Measurement System (FilmCheck AS300)

    • Commands for macOS and Ubuntu environment

      az dt twin create -n $ADT_NAME --dtmi "dtmi:itri:cms:filmcheck;1" --twin-id FilmCheck01 -g $RESOURCE_GROUP
      

      

• Initial Property

  • Commands for macOS and Ubuntu environment

    az dt twin update -n $ADT_NAME --twin-id FilmCheck01 --json-patch '[
    {"op":"add", "path":"/statusDate", "value": "0"},
    {"op":"add", "path":"/statusTime", "value": "0"},
    {"op":"add", "path":"/typeError", "value": -1},
    {"op":"add", "path":"/statusMessage", "value": "0"},
    {"op":"add", "path":"/statisticsDate", "value": "0"},
    {"op":"add", "path":"/statisticsTime", "value": "0"},
    {"op":"add", "path":"/statisticsStandardDeviation", "value": 0.0},
    {"op":"add", "path":"/statisticsAverage", "value": 0.0},
    {"op":"add", "path":"/statisticsUniformity", "value": 0.0},
    {"op":"add", "path":"/statisticsMax", "value": 0.0},
    {"op":"add", "path":"/statisticsMin", "value": 0.0},
    {"op":"add", "path":"/statisticsMaxMin", "value": 0.0}
    ]' -g $RESOURCE_GROUP
    

    

• Create Relationship

  • Commands for macOS and Ubuntu environment

    az dt twin relationship create -n $ADT_NAME --relationship-id DistCtr_contains_Relationship_FilmCheck01 --relationship contains --twin-id DistCtr --target FilmCheck01 -g $RESOURCE_GROUP
    

    

• List Relationship

  • Commands for macOS and Ubuntu environment

    az dt twin relationship list -n $ADT_NAME --twin-id DistCtr -g $RESOURCE_GROUP
    

    

• Check from Azure Digital Twins Explorer

  • Click the Open Azure Digital Twins Explorer (preview) button
  • After clicking on Run Query in the upper right corner, you will see the results.

5. Create Azure IoT Hub and Create IoT Device

• Create Azure IoT Hub

  • Commands for macOS and Ubuntu environment

    az iot hub create --resource-group $RESOURCE_GROUP --name $IOT_HUB_NAME --sku S1 --location $REGION
    

    

• Create IoT Device

  • Commands for macOS and Ubuntu environment

    az iot hub device-identity create --hub-name $IOT_HUB_NAME --device-id $IOT_DEVICE_NAME --resource-group $RESOURCE_GROUP
    

    

• Create 2 event hub consumer groups

  • Commands for macOS and Ubuntu environment

    az iot hub consumer-group create --hub-name $IOT_HUB_NAME --name $IOT_HUB_CONSUMER_GROUP_CONTAINER_APP --resource-group $RESOURCE_GROUP
    
    az iot hub consumer-group create --hub-name $IOT_HUB_NAME --name $IOT_HUB_CONSUMER_GROUP_STATIC_WEB_APP --resource-group $RESOURCE_GROUP
    

    

• Get FilmCheck01 IoT Device Connection String

  • Commands for macOS and Ubuntu environment

    az iot hub device-identity connection-string show --hub-name $IOT_HUB_NAME --device-id $IOT_DEVICE_NAME --output table --resource-group $RESOURCE_GROUP
    

    

6. Build Azure 3D Scenes Studio

• Create Storage Accounts & Container

  • Create Storage Account

    • Commands for macOS and Ubuntu environment

      az storage account create -n $BLOB_NAME -g $RESOURCE_GROUP -l $REGION --sku Standard_LRS
      

      

  • Create Container

    • Commands for macOS and Ubuntu environment

      az storage container create -n $BLOB_CONTAINER_NAME --account-name $BLOB_NAME --resource-group $RESOURCE_GROUP
      

      

  • Change access level

    • Commands for macOS and Ubuntu environment

      az storage container set-permission --name $BLOB_CONTAINER_NAME --public-access blob --account-name $BLOB_NAME
      

      

  • Add Storage Blob Data Owner

    • Retrieve the subscriptionId from the results.

      az account subscription list
      

      

    • Set parameter

      • Commands for macOS and Ubuntu environment

        export SUBSCRIPTION_ID="Enter the subscriptionId obtained in the previous step."
        
        echo $SUBSCRIPTION_ID
        

    • Create a role assignment.

      • Commands for macOS and Ubuntu environment

        az role assignment create \
            --role "Storage Blob Data Owner" \
            --assignee $USER_PRINCIPAL_NAME \
            --scope "/subscriptions/$SUBSCRIPTION_ID/resourceGroups/$RESOURCE_GROUP/providers/Microsoft.Storage/storageAccounts/$BLOB_NAME"
        

        

• Upload 3D Scenes to Studio & Create Twin

  • Enable Cross-Origin Resource Sharing (CORS) for storage account

    • Commands for macOS and Ubuntu environment

      az storage cors add --services b --methods GET OPTIONS POST PUT --origins https://explorer.digitaltwins.azure.net --allowed-headers Authorization x-ms-version x-ms-blob-type --account-name $BLOB_NAME
      

      

  • 3D Scenes Studio

    • Click the 3D Scenes button
    • Click on the pencil icon and Configure the instance and storage container details
    • Add a new 3D scene
      • Enter a Name and Description for your scene, and select the ./3D-Scenes/semi-v1.glb file for uploading.
    • After the file upload is completed, relevant information can also be viewed in the created blob.
    • Once the file is uploaded, you'll see it listed back on the main screen of 3D Scenes Studio
    • Select the scene to open and view it. The scene will open in Build mode
    • Create a scene element - Create the element for the Red color of the tri-color light
      • Select the floor in the scene visualization. This will bring up the possible element actions. Select + Create new element - Create the element for the Red color of the tri-color light
        • Display name, enter Display Red Status. Under Elements, select Floors.
        • Select Visual rules > Add Rule
        • Enter a Display name of Check Red Status. Leave the Property expression on Single property and open the property dropdown list. It contains names of all the properties on the primary twin for the Floor element. Select typeError. Then, select Add condition.
        • Add check typeError condition
          • Label name, enter Red.
          • Values Fields, Define a value range between 2 and 3 (the min range value is inclusive, and the max value is exclusive), and assign an Element coloring of Red. Select Save.
    • Create a scene element - Create the element for the Orange color of the tri-color light
      • Select the floor in the scene visualization. This will bring up the possible element actions. Select + Create new element - Create the element for the Orange color of the tri-color light
        • Display name, enter Display Orange Status. Under Elements, select Floors.
        • Select Visual rules > Add Rule
        • Enter a Display name of Check Orange Status. Leave the Property expression on Single property and open the property dropdown list. It contains names of all the properties on the primary twin for the Floor element. Select typeError. Then, select Add condition.
        • Add check typeError condition
          • Label name, enter Orange.
          • Values Fields, Define a value range between 1 and 2 (the min range value is inclusive, and the max value is exclusive), and assign an Element coloring of Orange. Select Save.
    • Create a scene element - Create the element for the Green color of the tri-color light
      • Select the floor in the scene visualization. This will bring up the possible element actions. Select + Create new element - Create the element for the Green color of the tri-color light
        • Display name, enter Display Green Status. Under Elements, select Floors.
        • Select Visual rules > Add Rule
        • Enter a Display name of Check Green Status. Leave the Property expression on Single property and open the property dropdown list. It contains names of all the properties on the primary twin for the Floor element. Select typeError. Then, select Add condition.
        • Add check typeError condition
          • Label name, enter Green.
          • Values Fields, Define a value range between 0 and 1 (the min range value is inclusive, and the max value is exclusive), and assign an Element coloring of Green. Select Save.
    • Create new element for display Statistics
      • Select the floor in the scene visualization. This will bring up the possible element actions. Select + Create new element
      • Display name, enter Display Statistics. Under Elements, select Floors.
      • Add Status widget
        • Select Widgets > Add widget
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of 機台狀態 and a Custom (advanced) Property expression of PrimaryTwin.typeError == 2 ? 目前機台發生錯誤, ${PrimaryTwin.statusMessage}: '目前機台正常運作', Type is string
      • Add Standard Deviation widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Standard Deviation and a Custom (advanced) Property expression of PrimaryTwin.statisticsStandardDeviation == 0 ? '目前尚無資料': PrimaryTwin.statisticsStandardDeviation, Type is double
      • Add Average widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Average and a Custom (advanced) Property expression of PrimaryTwin.statisticsAverage == 0 ? '目前尚無資料': PrimaryTwin.statisticsAverage, Type is double
      • Add Uniformity widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Uniformity and a Custom (advanced) Property expression of PrimaryTwin.statisticsUniformity == 0 ? '目前尚無資料': PrimaryTwin.statisticsUniformity, Type is double
      • Add Max widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Max and a Custom (advanced) Property expression of PrimaryTwin.statisticsMax == 0 ? '目前尚無資料': PrimaryTwin.statisticsMax, Type is double
      • Add Min widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Min and a Custom (advanced) Property expression of PrimaryTwin.statisticsMin == 0 ? '目前尚無資料': PrimaryTwin.statisticsMin, Type is double
      • Add Max Min widget
        • select Add widget.
        • Select the Value widget and select Add widget.
        • In the New widget options, add a Display name of Max Min and a Custom (advanced) Property expression of PrimaryTwin.statisticsMaxMin == 0 ? '目前尚無資料': PrimaryTwin.statisticsMaxMin, Type is double
        • click Create behavior
    • View scene
      • So far, you've been working with 3D Scenes Studio in Build mode. Now, switch the mode to View.

7. Setting up notifications to be sent through Microsoft Teams

• Click the 建立團隊 button

• Click the 其他 button

• Please enter a unique and identifiable name in the 團隊名稱 field, and click 下一步 after you have finished entering it.

• During the team creation process

• Click the 略過 button

• Creation completed

• Click the 連接器 button in the ... menu at the top right corner. (The 連接器 option will appear in a moment, please wait.)

• Click the 新增 button on the right side of 傳入 Webhook

• Click the 新增 button

• Click the 連接器 button in the ... menu at the top right corner

• Click the 設定 button on the right side of 傳入 Webhook

• Please enter a unique and identifiable name in the Incoming Webhook field, and click 建立 after you have finished entering it.

• After creation is completed, please copy the URL and then click the 完成 button

  • Commands for macOS and Ubuntu environment

    export WEBHOOK_URL='Paste the copied URL'
    
    echo $WEBHOOK_URL
    

    

• Configuration completed

8. Database environment setup and configuration

• Create a server

  • Commands for macOS and Ubuntu environment

    az postgres server create --name $DB_PG_NAME --resource-group $RESOURCE_GROUP --location $REGION --admin-user $DB_USER_NAME --admin-password $DB_USER_PASSWORD --sku-name $DB_SKU --version 11 --ssl-enforcement Enabled
    

    

• Allow access to Azure Services

  • Commands for macOS and Ubuntu environment

    az postgres server firewall-rule create --resource-group $RESOURCE_GROUP \
      --server-name "$DB_PG_NAME" \
      --name "allow-azure-internal" \
      --start-ip-address 0.0.0.0 \
      --end-ip-address 0.0.0.0
    

    

• Get the local IP address.

  • Commands for Local environment

    export LOCAL_IP=`curl ifconfig.me`
    
    echo $LOCAL_IP
    

    

• Configure a server-based firewall rule

  • Commands for macOS and Ubuntu environment

    az postgres server firewall-rule create --resource-group $RESOURCE_GROUP --server $DB_PG_NAME --name AllowLocalIp --start-ip-address $LOCAL_IP --end-ip-address $LOCAL_IP
    

    

• Get the server name and the admin username

• Create a database

  • Open the pgAdmin software
  • Right-click the Servers button > Click the Register button > Click the Server... button
  • Enter a recognizable name in the Name field
  • Enter relevant information on the Connection tab
    • In the Host name field, enter the Server name obtained from the Get the server name and the admin username section.
    • In the Username field, enter the Admin username obtained from the Get the server name and the admin username section.
    • In the Password field, enter the password you have set.
    • After entering the above information, click the Save button.
    • If login fails, please reset your password.
  • Establish FilmCheck Database
    • Right-click the Databases button > Click the Create button > Click the Database... button
    • Enter FilmCheck in the Database field.
    • After entering the above information, click the Save button.
    • Completion screen created

• Create the Log and Report Table

  • Switch working directory

    cd ./AzureContainerApp/DB_Ops
    

  • Install required packages

    npm i
    

    

  • Modify the content of development in the config/config.json file (username、password、database)

  {
    "development": {
      "username": "Please modify it with the information obtained earlier.",
      "password": "Please modify it with the information obtained earlier.",
      "database": "Please modify it with the information obtained earlier.",
      "host": "Please modify it with the information obtained earlier.",
      "dialect": "postgres",
      "ssl": true,
      "dialectOptions": {
        "ssl": {
          "require": true
        }
      }
    },
  }

  • Create the Tables

    npx sequelize db:migrate --env development
    

    

  • Open Query Tool

    • Right-click on the created database > Click the Query Tool

    • Query Tool

  • Check the Log Table

    SELECT * FROM public."Logs"

    

  • Check the Report Table

    SELECT * FROM public."Reports"

    

  • Check the Status Table

    SELECT * FROM public."Statuses"

    

9. Deploy the Azure Container App

• Upgrade the Azure CLI

az upgrade
az config set auto-upgrade.enable=yes
az extension add --name containerapp --upgrade

• Create an Azure Container Registry

  • Commands for macOS and Ubuntu environment

    az acr create \
      --resource-group $RESOURCE_GROUP \
      --name $ACR_NAME \
      --sku Basic \
      --admin-enabled true
    

    

• List the container registries under the current subscription

  • Commands for macOS and Ubuntu environment

    az acr list \
      -o table \
      -g $RESOURCE_GROUP
    

    

• Log in to the Azure Container Registry

  • Commands for macOS environment

    az acr login --name $ACR_NAME
    

    

  • Commands for Ubuntu environment

    az acr credential show --name containerforacr.azurecr.io --query passwords[0].value --output tsv
    
    sudo az acr login --name $ACR_NAME
    
    Username: containerforacr
    Password: Please enter the result obtained from the command 'az acr credential show'
    

    

• Switch working directory (IoT Hub To ADT)

cd ../IoTHub_To_ADT_Notify

• Modify the content of development in the config/config.json file (username、password、database)

  {
    "development": {
      "username": "Please modify it with the information obtained earlier.",
      "password": "Please modify it with the information obtained earlier.",
      "database": "Please modify it with the information obtained earlier.",
      "host": "Please modify it with the information obtained earlier.",
      "dialect": "postgres",
      "ssl": true,
      "dialectOptions": {
        "ssl": {
          "require": true
        }
      }
    },
  }

• Create a Docker Image (IoT Hub To ADT)

  • Commands for macOS and Ubuntu environment

    sudo docker buildx build . --platform linux/amd64 --push -t $ACR_NAME.azurecr.io/hub-to-adt-notify:0.1 -f docker-manifests/Dockerfile
    

    

• Check Azure container registry from Browser

• Create a Container Apps Environments (IoT Hub To ADT)

  • Commands for macOS and Ubuntu environment

    az containerapp env create \
      --name $ACA_ENVIRONMENT_HUB \
      --resource-group $RESOURCE_GROUP \
      --location $REGION
    

    

• Get default Domain (IoT Hub To ADT)

  • Commands for macOS and Ubuntu environment

    az containerapp env show \
      --name $ACA_ENVIRONMENT_HUB \
      --resource-group $RESOURCE_GROUP
    

    

• Set parameters

  • Get Build-in Event Hub-compatible endpoint

    • Commands for macOS and Ubuntu environment

      az iot hub connection-string show --hub-name $IOT_HUB_NAME --default-eventhub --resource-group $RESOURCE_GROUP --query connectionString
      
      export EVENTHUB_CONNECTION_STRING="Enter the connectionString obtained in the previous step."
      
      echo $EVENTHUB_CONNECTION_STRING
      

      

  • Get Azure Digital Twin Host URL

    • Commands for macOS and Ubuntu environment

    az dt show --dt-name $ADT_NAME --resource-group $RESOURCE_GROUP --query hostName
    
    export ADT_Host_Name="Enter the Azure Digital Twin Host URL obtained in the previous step."
    
    echo $ADT_Host_Name
    

    

• Confirm parameters

  echo $ADT_NAME
  echo $IOT_HUB_CONSUMER_GROUP_CONTAINER_APP
  echo $EVENTHUB_CONNECTION_STRING
  echo $ADT_Host_Name
  echo $WEBHOOK_URL
  

  

• Deploy the image to Azure Container App (IoT Hub To ADT)

  • Commands for macOS and Ubuntu environment

    az containerapp create \
      --name $ACA_NAME_HUB \
      --resource-group $RESOURCE_GROUP \
      --environment $ACA_ENVIRONMENT_HUB \
      --registry-server $ACR_NAME.azurecr.io \
      --image $ACR_NAME.azurecr.io/hub-to-adt-notify:0.1 \
      --env-vars "EVENTHUB_NAME=secretref:eventhub-name" "CONSUMER_GROUP_NAME=secretref:consumer-group-name" "EVENTHUB_CONNECTION_STRING=secretref:eventhub-connection-string" "ADT_Host_Name=secretref:adt-host-name" "WEBHOOK_URL=secretref:webhook-url" \
      --secrets "eventhub-name=$ADT_NAME" "consumer-group-name=$IOT_HUB_CONSUMER_GROUP_CONTAINER_APP" "eventhub-connection-string=$EVENTHUB_CONNECTION_STRING" "adt-host-name=$ADT_Host_Name" "webhook-url=$WEBHOOK_URL" \
      --min-replicas 1 \
      --max-replicas 1 \
      --ingress 'internal' \
      --target-port 3000 \
      --query properties.configuration.ingress.fqdn
    
    "adt3dhub.internal.proudsky-415d04fa.japaneast.azurecontainerapps.io"
    

    

• Set role assignment

  • Enable System assigned

    • Commands for macOS and Ubuntu environment

      az containerapp identity assign -g $RESOURCE_GROUP -n $ACA_NAME_HUB --system-assigned
      

      

  • Add role assignment

    • Click on the created adt3dhub in the Container App on the Azure portal > Click on Identity in the left-hand menu > Click on Azure role assignments

    • Click on the + Add role assignment (Preview) button

      • Enter the relevant information
        • Select Subscription in the Scope field.
        • Select the desired subscription in the Subscription field.
        • Select Azure Digital Twins Data Owner in the Role field.
        • After entering the above information, click on the Save button.

• Switch working directory (Query ADT)

cd ../Query_ADT

• Create a Container Apps Environments (Query ADT)

  • Commands for macOS and Ubuntu environment

    az containerapp env create \
      --name $ACA_ENVIRONMENT_QUERY \
      --resource-group $RESOURCE_GROUP \
      --location $REGION
    

    

• Get default Domain (Query ADT)

  • Commands for macOS and Ubuntu environment

    az containerapp env show \
      --name $ACA_ENVIRONMENT_QUERY \
      --resource-group $RESOURCE_GROUP
    

    

• Create the Query ADT Docker Image (Query ADT)

  • Commands for macOS and Ubuntu environment

    sudo docker buildx build . --platform linux/amd64 --push -t $ACR_NAME.azurecr.io/query-adt:0.2 -f docker-manifests/Dockerfile
    

    

• Confirm parameters

  • Commands for macOS and Ubuntu environment

    echo $ADT_Host_Name
    
    export ADT_Host_Name="adt-3d.api.jpe.digitaltwins.azure.net"
    

    

• Deploy the Query ADT image to Azure Container App (Query ADT)

  • Please remember the URL returned after executing the command.

    • Commands for macOS and Ubuntu environment

      az containerapp create \
        --name $ACA_NAME_QUERY \
        --resource-group $RESOURCE_GROUP \
        --environment $ACA_ENVIRONMENT_QUERY \
        --registry-server $ACR_NAME.azurecr.io \
        --image $ACR_NAME.azurecr.io/query-adt:0.2 \
        --env-vars "ADT_Host_Name=secretref:adt-host-name" \
        --secrets "adt-host-name=$ADT_Host_Name" \
        --min-replicas 1 \
        --max-replicas 1 \
        --ingress 'external' \
        --target-port 80 \
        --query properties.configuration.ingress.fqdn
      
      "adt3dquery.kindpebble-e066fde2.japaneast.azurecontainerapps.io"
      

      

• Set parameter

  • Commands for macOS and Ubuntu environment

    export QUERY_ADT_URL="Enter the URL obtained in the previous step."
    
    echo $QUERY_ADT_URL
    

• Set role assignment (Query ADT)

  • Enable System assigned

    • Commands for macOS and Ubuntu environment

      az containerapp identity assign -g $RESOURCE_GROUP -n $ACA_NAME_QUERY --system-assigned
      

      

  • Add role assignment

    • Click on the created adt3dquery in the Container App on the Azure portal > Click on Identity in the left-hand menu > Click on Azure role assignments

    • Click on the + Add role assignment (Preview) button

      • Enter the relevant information
        • Select Subscription in the Scope field.
        • Select the desired subscription in the Subscription field.
        • Select Azure Digital Twins Data Owner in the Role field.
        • After entering the above information, click on the Save button.

• Test (Query ADT)

https://adt3dquery.kindpebble-e066fde2.japaneast.azurecontainerapps.io/hello

https://adt3dquery.kindpebble-e066fde2.japaneast.azurecontainerapps.io/adt/query/statistics

• Switch working directory (DB Ops)

cd ../DB_Ops

• Modify the content of development in the config/config.json file (username、password、database)

  {
    "development": {
      "username": "Please modify it with the information obtained earlier.",
      "password": "Please modify it with the information obtained earlier.",
      "database": "Please modify it with the information obtained earlier.",
      "host": "Please modify it with the information obtained earlier.",
      "dialect": "postgres",
      "ssl": true,
      "dialectOptions": {
        "ssl": {
          "require": true
        }
      }
    },
  }

• Create the Query ADT Docker Image (DB Ops)

  • Commands for macOS and Ubuntu environment

    sudo docker buildx build . --platform linux/amd64 --push -t $ACR_NAME.azurecr.io/db-ops:0.1 -f docker-manifests/Dockerfile
    

    

• Create a Container Apps Environments (DB Ops)

  • Commands for macOS and Ubuntu environment

    az containerapp env create \
      --name $ACA_ENVIRONMENT_DB_OPS \
      --resource-group $RESOURCE_GROUP \
      --location $REGION
    

    

• Deploy the Query ADT image to Azure Container App (DB Ops)

  • Please remember the URL returned after executing the command.

    • Commands for macOS and Ubuntu environment

      az containerapp create \
        --name $ACA_NAME_DB_Ops \
        --resource-group $RESOURCE_GROUP \
        --environment $ACA_ENVIRONMENT_DB_OPS \
        --registry-server $ACR_NAME.azurecr.io \
        --image $ACR_NAME.azurecr.io/db-ops:0.1 \
        --min-replicas 1 \
        --max-replicas 1 \
        --ingress 'external' \
        --target-port 80 \
        --query properties.configuration.ingress.fqdn
      
      "dbops.victoriousground-728f9a8f.japaneast.azurecontainerapps.io"
      

      

• Set parameter

  • Commands for macOS and Ubuntu environment

    export DB_OPS_API_URL="Enter the URL obtained in the previous step."
    
    echo $DB_OPS_API_URL
    

• Test (DB Ops)

  • https://DB_OPS_API_URL/logs
  • https://DB_OPS_API_URL/reports
  • https://DB_OPS_API_URL/status/latest
  • https://DB_OPS_API_URL/reports/latest

10. Deploying the Frontend to Azure Static Web Apps

• Deploy files from the ./Azure-Digital-Twins-End-To-End-Sample/Frontend folder to GitHub.

• Click the Settings > Click the Secrets and variables > Click the Actions > Click the New repository secret

• Add the following secret

  • Add VUE_APP_EVENTHUB_NAME

    • Enter VUE_APP_EVENTHUB_NAME in the Name field.
    • Enter the string displayed by echo $ADT_NAME in the Secret field.
    • After entering the above information, click the Add secret button.

  • Add VUE_APP_CONSUMER_GROUP_NAME

    • Enter VUE_APP_CONSUMER_GROUP_NAME in the Name field.
    • Enter the string displayed by echo $IOT_HUB_CONSUMER_GROUP_STATIC_WEB_APP in the Secret field.
    • After entering the above information, click the Add secret button.

  • Add VUE_APP_EVENTHUB_CONNECTION_STRING

    • Get Build-in Event Hub-compatible endpoint

      az iot hub connection-string show --hub-name $IOT_HUB_NAME --default-eventhub --resource-group $RESOURCE_GROUP --query connectionString
      

      

    • Add Secret

      • Enter VUE_APP_EVENTHUB_CONNECTION_STRING in the Name field.
      • Enter the result displayed in the previous step in the Secret field.
      • After entering the above information, click the Add secret button.

  • Add VUE_APP_API_URL (ACA - DB Ops)

    

    • Enter VUE_APP_API_URL in the Name field.
    • Enter the string displayed by echo $DB_OPS_API_URL in the Secret field.
    • After entering the above information, click the Add secret button.

  • Add VUE_APP_BLOB_NAME

    

    • Enter VUE_APP_BLOB_NAME in the Name field.
    • Enter the string displayed by echo $BLOB_NAME in the Secret field.
    • After entering the above information, click the Add secret button.

  • Add VUE_APP_QUERY_ADT_URL (ACA - Query ADT)

    

    • Enter VUE_APP_QUERY_ADT_URL in the Name field.
    • Enter the string displayed by echo $QUERY_ADT_URL in the Secret field.
    • After entering the above information, click the Add secret button.

• Enter Static Web App in the search box of the Azure Portal. > Select the search result for Static Web Apps.

• Click the + Create button at the top.

• Enter the relevant information.

• Confirm the entered information.

• Creation completed.

• After modifying ./ADT_Web/tree/main/.github/workflows/azure-static-web-apps-Random-Number.yml, commit the changes (You can see this file from the GitHub repository). Add the information in the env: section below (Please align the format).

  jobs:
    build_and_deploy_job:
      if: ...
      runs-on: ubuntu-latest
      name: Build and Deploy Job
      steps:
        - uses: actions/checkout@v2
          with:
            submodules: true
        - name: Build And Deploy
          id: builddeploy
          uses: Azure/static-web-apps-deploy@v1
          with:
            ...
          env:
            VUE_APP_EVENTHUB_NAME: ${{ secrets.VUE_APP_EVENTHUB_NAME }}
            VUE_APP_CONSUMER_GROUP_NAME: ${{ secrets.VUE_APP_CONSUMER_GROUP_NAME }}
            VUE_APP_EVENTHUB_CONNECTION_STRING: ${{ secrets.VUE_APP_EVENTHUB_CONNECTION_STRING }}
            VUE_APP_API_URL: ${{ secrets.VUE_APP_API_URL }}
            VUE_APP_BLOB_NAME: ${{ secrets.VUE_APP_BLOB_NAME }}
            VUE_APP_QUERY_ADT_URL: ${{ secrets.VUE_APP_QUERY_ADT_URL }}

• Confirm the status from GitHub actions.

• Obtain the URL of the Static Web App.

11. Launching the program on the Edge

• Download the zip file of the source code to the edge and unzip it..

  • Please refer to the instructions on how to download the zip file of the source code.

• Install Mosquitto MQTT Broker On Ubuntu Edge

sudo apt update 
sudo apt install -y mosquitto

• Change directory

cd ./Edge

• Install Python packages with pip and requirements.txt

pip3 install -r requirements.txt

• Get FilmCheck01 IoT Device Connection String

az iot hub device-identity connection-string show --hub-name $IOT_HUB_NAME --device-id $IOT_DEVICE_NAME --output table --resource-group $RESOURCE_GROUP

• Get the Connection string for the blob

  • Perform operations on the created blob.

• Get the container name for the blob

  • Perform operations on the created blob.

• Create .env File and Add the following information.

IOT_HUB_DEVICE_CONNECTION_STRING="Enter the result obtained from the Get FilmCheck01 IoT Device Connection String."
BLOB_CONNECTION_STRING="Enter the result obtained from the Get the Connection string for the blob."
BLOB_CONTAINER_NAME="Enter the result obtained from the Get the container name for the blob."

• Run Code

python3 edge.py

• After receiving the log information from FilmCheck AS300, Edge will store the log information locally and upload it to Azure Blob at 5:00 every day. Similarly, upon receiving the report information from FilmCheck AS300, Edge will store the report information locally and upload it to Azure Blob in real-time.

12. Launch the program for FilmCheck AS300

• FilmCheck AS300 operation screen

13. Confirming the results from Azure Digital Twins 3D Scenes Studio

14. Confirming the results from the Frontend

• Machine idle

• Machine running

• Machine malfunction

• Machine statistics information

15. Confirming the results from the Microsoft HoloLens

16. Analysis and Learning of Film Thickness Data

• Enter Azure Machine Learning in the search box above and click on Azure Machine Learning in the search results.

• Click on the + Create button in the upper left corner. > Then click on New Workspace.

• Enter the relevant information.

• After verifying the relevant information, click on Create in the lower left corner.

• During the creation process.

• After the creation is completed, please click on Go to resource.

• Click on Launch studio.

• Click on Compute on the left side to create a compute resource.

• Click on the + New button below.

• After selecting the desired CPU or GPU specifications, click on Create below.

• During the creation process

• Click on Notebooks in the upper left corner.

• Create a notebook.

  • Click on the ⊕ symbol. > Then click on Upload folder.

  • Click on Click to browse and select folder(s).

  • Upload the files from the Azure-Digital-Twins-End-To-End-Sample/AzureML.

  • Click on Upload.

  • Click on Upload.

  • Upload completed.

• Click on run_pipeline.ipynb.

• Click on the Python 3.8 - AzureML execution environment in the upper right corner (green light indicates it is running).

• Confirm that the Compute instance is running (green light indicates it is running).

• The relevant code

  • Execute the 安裝套件與確認 SDK 版本 code block.

    • Click on the left side ▷ symbol.
    • The execution result

  • Execute the 配置工作環境 code block.

    • Click on the left side ▷ symbol.
    • The execution result

  • Execute the 連接已有的 Blob code block.

    • Modify lines 3, 4, and 5.

      • Replace the right-hand side of the equal sign in line 3 with the obtained Storage account name.

      • Replace the right side of the equal sign in line 4 with the obtained Key.

      • Replace the right-hand side of the equal sign in line 5 with the created blob container.

    • Click on the left side ▷ symbol.

    • The execution result

  • Execute the 建立運算叢集 code block.

    • Click on the left side ▷ symbol.
    • The execution result

  • Execute the 設定執行環境的 config code block.

    • Click on the left side ▷ symbol.
    • The execution result

  • Execute the 建立 Python 腳本步驟 code block.

    • Click on the left side ▷ symbol.
    • The execution result

  • Execute the 部署成 pipeline 與儲存 pipeline ID code block.

    • Click on the left side ▷ symbol.
    • The execution result

• Create an AzureML Pipeline that is triggered when a report file is uploaded to Blob.

  • Click on the Pipelines button on the left-hand side. > Click on the Pipeline endpoints button at the top. > Click on the blob-trigger-pipeline.

  • Copy the URL under REST endpoints

  • Set parameters

    • EXPERIMENT_NAME

      • Commands for macOS and Ubuntu environment

        export EXPERIMENT_NAME='blob-trigger-pipeline'
        echo $EXPERIMENT_NAME
        

        

    • TRIGGER_ML_ENDPOINT

      • Commands for macOS and Ubuntu environment

        export TRIGGER_ML_ENDPOINT='the REST endpoint URL obtained earlier'
        echo $TRIGGER_ML_ENDPOINT
        

        

  • Switch working directory (Blob Trigger)

    cd ../Blob_Trigger
    

  • Modify the content of development in the config/config.json file (username、password、database)

    {
      "development": {
        "username": "Please modify it with the information obtained earlier.",
        "password": "Please modify it with the information obtained earlier.",
        "database": "Please modify it with the information obtained earlier.",
        "host": "Please modify it with the information obtained earlier.",
        "dialect": "postgres",
        "ssl": true,
        "dialectOptions": {
          "ssl": {
            "require": true
          }
        }
      },
    }

  • Create a Blob Trigger Container Apps Environments (Blob Trigger)

    • Commands for macOS and Ubuntu environment

      az containerapp env create \
        --name $ACA_ENVIRONMENT_BLOB \
        --resource-group $RESOURCE_GROUP \
        --location $REGION
      

      

  • Get default Domain (Blob Trigger)

    • Commands for macOS and Ubuntu environment

      az containerapp env show \
        --name $ACA_ENVIRONMENT_BLOB \
        --resource-group $RESOURCE_GROUP
      

      

  • Create the Blob Trigger Docker Image (Blob Trigger)

    • Commands for macOS and Ubuntu environment

      sudo docker buildx build . --platform linux/amd64 --push -t $ACR_NAME.azurecr.io/blob-trigger:0.1 -f docker-manifests/Dockerfile
      

      

  • Deploy the Blob Trigger image to Azure Container App (Blob Trigger)

    • Commands for macOS and Ubuntu environment

      az containerapp create \
        --name $ACA_NAME_BLOB \
        --resource-group $RESOURCE_GROUP \
        --environment $ACA_ENVIRONMENT_BLOB \
        --registry-server $ACR_NAME.azurecr.io \
        --image $ACR_NAME.azurecr.io/blob-trigger:0.1 \
        --env-vars "EXPERIMENT_NAME=secretref:experiment-name" "TRIGGER_ML_ENDPOINT=secretref:trigger-ml-endpoint" \
        --secrets "experiment-name=$EXPERIMENT_NAME" "trigger-ml-endpoint=$TRIGGER_ML_ENDPOINT" \
        --min-replicas 1 \
        --max-replicas 1 \
        --ingress 'external' \
        --target-port 80 \
        --query properties.configuration.ingress.fqdn
      
      "blobtrigger.ashysky-edb6ddb2.japaneast.azurecontainerapps.io"
      

      

  • URL obtained after Azure Container App for Blob Trigger is created.

  • Set Azure role assignments in the Azure Container App where the Blob Trigger was created. (ACA-blobtrigger)

    • Click on the Identity on the left-hand side. > Click on the System assigned tab. > Set the Status to On. > Click the Save button.

    • Click on Yes.

    • Click on Azure role assignments.

    • Click on the + Add role assignment (Preview) button above.

    • Enter relevant information.

      • Please select Subscription in the Scope field.
      • Select AzureML Data Scientist for the Role field.
      • After entering the above information, please click on Save.

    • Input completed.

  • Set up the Web hook to be triggered when a Blob is added.

    • Click on the Events on the left side. > Then click on More Options. > Click on Web Hook.

    • Enter relevant information.

      • In the Name field, please enter a unique and identifiable name.
        • This example uses blob-event-subscription.
      • In the System Topic Name field, please enter a unique and identifiable name.
        • This example uses blob-event-topic.
      • In the Filter to Event Types field, please select Blob Created and Blob Deleted.
      • In the Endpoint Type field, please select Web Hook.
      • In the Endpoint field, please enter the URL obtained from the previous section URL obtained after Azure Container App for Blob Trigger is created.
      • After completing the above information, please click on the Create button at the bottom left corner.

  • Upload csv file through Edge to the created Blob to confirm that the pipeline has been triggered.

    • The uploaded completed CSV file will be in the Storage accounts > adt3dstorageaccount > Containers > adt > Report.
    • Verify the Azure Machine Learning Pipeline.
      • Pipeline is executing.
      • Pipeline has completed execution.

  • Check Metrics and Image

    • Click on the Job overview button located on the top right corner.
    • Click on Metrics
    • Metrics Result
    • Click on Images

  • Verify that the result file added by the pipeline earlier has been added to the Image folder in the created Blob.

    • Search for Storage accounts > adt3dstorageaccount > Containers > adt > Image

Reference

• https://learn.microsoft.com/en-us/azure/digital-twins/quickstart-3d-scenes-studio
• https://learn.microsoft.com/en-us/azure/digital-twins/how-to-use-3d-scenes-studio#use-custom-advanced-expressions
• https://learn.microsoft.com/en-us/rest/api/azure-digitaltwins/#data-plane

Contributors

• Huang, Cheng-Chuan
• Huang, Jui-Feng
• Luo, Jun-Wei
• Wei, Hsiang-Chun
• Wei, Shao-Chun

License

Examples of Azure Digital Twins is licensed under the MIT license.