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.
Creating an AI Model
To build an AI model, you press the Model button in the capture list.
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.
Training the AI
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 several files…
- model.keras
- model.json
- ardiai.py
- run.py
Copy all of these files onto your ARDI server, in the same folder as your config.json file.
From now on, when users click on the Model button in the capture list, they'll be able to run queries on the AI model.