AI Prediction

AI Prediction is used when you want to try to predict what specific capture values should be based on other capture values.

Most often, you're trying to predict a result from something you know before-hand, such as…

• Determining product quality from the current system state,
• Calculating an ideal system setup based on the next product information, or
• Calculating a virtual sensor value based on manual recordings.

See AI vs Fuzzy Matching for a discussion on some key benefits and down-sides of using AI vs using a 'lookup' or 'fuzzy matching' technique.

A single type of Capture may have several different AI models, each answering a different type of question.

To build an AI model, you press the AI Model button under Search in the capture list.

Then - as an Administrator - press Add New AI Model.

You'll then be prompted to select the inputs and outputs of your model. The inputs are the things you're going to know ahead of time, and the outputs are the things you want to know.

In our example cupcake bakery, the things we would know before or during production would be…

• Product Weight,
• Product Type (ie. Blueberry, Chocolate, Bananna).
• Product Style (ie, Plain, Deluxe, Fudgy, Gluten Free),
• Ambient Temperature
• Ambient Humidity

…while the things we want to know - that are normally measured by our QA team - will be…

• Surface Darkness,
• Internal Temperature,
• Texture/Crumble,
• QA Pass or Fail

Once these are all selected, press the button to build the AI.

A ZIP file will be downloaded.

The ZIP file contains almost everything you need to build an AI model.

Training AI takes a considerable amount of computing power and time.

Because ARDI servers are often used for applications where data timing is important, we don't suggest training complex AIs on the ARDI server itself. Instead, we give you the tools needed to build the AI on any machine of your choice.

See Building an AI Model for more details of the process.

Once your AI has been trained, you'll have two important files.

• model.keras
• model.json

Go back to the Capture addon, go to Search|AI Model, and press the Upload New AI Model button.

Here you'll be able to create a name for your AI model (describing what the model does, such as 'Predict Quality Outcomes') and fields to upload both your keras and json files.

Once you press Upload, the files will be updated and you'll be able to run the model from the list.

To make your AI run live - automatically updating with the rest of your process data - you can Create a ModelHost Service.