Getting started with Computer Vision AI / ML — Tutorial Step 5 of 7: Set up Gravio Coordinator and connect HubKit to it

In this tutorial, we learn how to create a system to detect if a sink contains any dishes that need washing up. This is step 5 of 7. Start with Step 1 here, or view the full tutorial on

Steps to get into Machine Learning and Computer Vision

  1. Collecting images of as many different situations as possible (Details)
  2. Setting up your Google Cloud Vision account (Details)
  3. Uploading and labeling those images via the Google Vision AI website, training the Model (Details)
  4. Download the model from Google’s platform (Details)
  5. Set up Gravio Coordinator and connect HubKit to it 👈 YOU ARE HERE
  6. Deploy the model to Gravio Coordinator and subsequently to HubKit (Details)
  7. Create Actions that are being triggered based on what the camera sees (Details)

Step 5 — Set up Gravio Coordinator and connect HubKit to it

In order to deploy the models to your edge nodes, you will need to have access to an Enterprise edition of Gravio. The Enterprise edition comes with the “Gravio Coordinator” which will host your models. From there you can deploy them to the various edge nodes.

The Gravio Coordinator can be installed on any Linux machine, on-premise or on a (private) cloud. Find out more about installing the Gravio Coordinator here:

In a nutshell, if you have a raspberry pi, you can install Gravio including the coordinator by:

  1. Downloading the latest .deb file from the website
  2. Run “sudo apt install -y ./setup_-XXXX_XXX64.deb
  3. Wait for the system to completely install. Detailed instructions can be found on
  4. Once it’s installed, you can open the IP address of your machine, create an account, log in with that account and click on “License” to retrieve your license from your account:

You can also just upload a license file, you will receive from Asteria.

Congratulations, your Coordinator is now installed and your Edge devices are ready to be connected to the Coordinator.

Now let’s connect your Edge HubKits (edge computing server or servers, if you have multiple) to the Coordinator. First, start Gravio Studio, which you can download from the Apple or Windows App store. Instead of creating an account and logging in, you can now log in with the credentials you have just created on Gravio Coordinator. For this, click on the “Log in” button

And then click on “Log in with Gravio Coordinator”

Here you can enter the IP of your coordinator and log in using the account you have created on your Coordinator:

Once logged in, you can see all Gravio HubKits in your network. Click on the one you would like to connect to the Coordinator, and navigate to the Settings and copy your Hub ID:

Go back to your Coordinator and click on the “Hub” tab and click “Add”:

Note, here I have previously added other devices to this Coordinator. But yours is likely to be empty in the beginning.

You can then enter the details of your HubKit including the ID you have copied earlier:

Set a password for the communication between the HubKit and the Coordinator to authenticate with. If you like, you can also enable Blockchain so this HubKit will become part of a Distributed Ledger Technology system. Click “Save” and enter the same password into the password field of your HubKit:

You can then test the Login by clicking on “Test Login”:

You should see a success message. Your Coordinator is now connected with your Edge server HubKit.

This means, if you deploy a model to your Coordinator, it will be available in your Gravio Hub connected to the same Coordinator.

That’s it, you’re ready to deploy the model to the actual coordinator ready for distribution on your edge devices. In the following steps we will show you how to deploy them on the Gravio Edge Computing infrastructure.

Continue to the next Step: Deploy the model to Gravio Coordinator and subsequently to HubKit

Join our Slack if you have questions.

Go to the full A-Z tutorial on




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Christoph Burgdorfer

Christoph Burgdorfer

Technology. Design. User Experience. IoT. Switzerland ~ London ~ Hong Kong

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