This project contains the code necessary to setup either (1) a Raspberry Pi with a heart rate sensor or (2) a Google Cloud Compute Engine VM with a data simulation script in order to demonstrate how Google Cloud IoT Core works. The full instructions are contained this Codelab (https://g.co/codelabs/iotcore-heartrate). The instructions below provide the gcloud commands which are parallel to the Cloud Console UI instructions that are given in the Codelab.

NOTE: Replace PROJECT_ID with your project in the following commands

1. Login to Google Cloud. If desired, create a new project and select it once it is ready. Open a Cloud shell.

2. Enable the necessary APIs

    gcloud services enable compute.googleapis.com
    gcloud services enable dataflow.googleapis.com
    gcloud services enable pubsub.googleapis.com
    gcloud services enable cloudiot.googleapis.com
   

3. Create a BigQuery dataset and table:

    bq --location=US mk --dataset PROJECT_ID:heartRateData
    bq mk --table PROJECT_ID:heartRateData.heartRateDataTable sensorID:STRING,uniqueID:STRING,timecollected:TIMESTAMP,heartrate:FLOAT
   

   In the case the table needs to be deleted (i.e. in order to be recreated)...

    bq rm -t -f PROJECT_ID:heartRateData.heartRateDataTable
   

4. Create a PubSub topic:

    gcloud beta pubsub topics create projects/PROJECT_ID/topics/heartratedata
   

5. Create a Dataflow process:

    Calling Google-provided Dataflow templates from the command line is not yet supported. 
    Follow the Codelab to do so via the Cloud Console.
   

6. Create a registry:

    gcloud beta iot registries create heartrate \
        --project=PROJECT_ID \
        --region=us-central1 \
        --event-pubsub-topic=projects/PROJECT_ID/topics/heartratedata
   

7. Create a VM

    gcloud compute instances create data-simulator-1 --zone us-central1-c
   

8. Connect to the VM. Install the necessary software and create a security certificate. Note the full path of the directory that the security certificate is stored in (the results of the "pwd" command). Then exit the connection.

    gcloud compute ssh data-simulator-1
    sudo apt-get update
    sudo apt-get install git
    git clone https://github.com/sunsetmountain/iotcore-heartrate
    cd iotcore-heartrate
    chmod +x initialsoftware.sh
    ./initialsoftware.sh
    chmod +x generate_keys.sh
    ./generate_keys.sh
    cd ../.ssh
    pwd
    exit
   

9. Use SCP to copy the public key that was just generated. The path the SSH keys was the result of the "pwd" command in the previous step.

    gcloud compute scp data-simulator-1:/[PATH TO SSH KEYS]/ec_public.pem .
   

10. Register the VM as an IoT device:

    gcloud beta iot devices create myVM \
        --project=PROJECT_ID \
        --region=us-central1 \
        --registry=heartrate \
        --public-key path=ec_public.pem,type=es256
    

11. Connect to the VM. Send the mock data (data/SampleData.json) using the simulateData.py script. This publishes several hundred JSON-formatted messages to the device's MQTT topic one by one:

    gcloud compute ssh data-simulator-1
    cd iotcore-heartrate
    python heartrateSimulator.py --registry_id=heartrate --project_id=PROJECT_ID --device_id=myVM --private_key_file=../.ssh/ec_private.pem
    exit
    

    Exit from the Cloud Shell

    exit
    

12. Go to BigQuery, query the data and export it to Google Sheets.

13. After you are done, clean everything up

    gcloud dataflow jobs list
    gcloud dataflow jobs cancel [JOB_ID]
    bq rm -r PROJECT_ID:heartRateData
    gcloud beta pubsub topics delete heartratedata
    gcloud beta iot devices list --registry=heartrate --region=us-central1
    gcloud beta iot devices delete [DEVICE_ID]
    gcloud beta iot registries delete heartrate --region=us-central1
    gcloud compute instances delete data-simulator-1