📺 Watch the Video View on YouTube --- Machine Learning in WIO Terminal (Seeed Studio) to recognize shake and roll two die using True Random Number Ge...
•Generate appropiate labels for each data point, click on start sampling. When the countdown starts, perform appropiate action on the WIO based on the label given
•Once a 10s data collection is complete, check the collected data section and click on hamberger icon and split sample
•Split the sample into 1s chunks and click split
•Repeat to have lots of data for each label
•Do the same for Test data (top-left) for each label
3. Create Impulse & Process/Clean up data & training NN
•Create a new impulse (overall design of the project)
•Generate Spectral Features - clean up your raw accelerometer data
•Generate Features
•Train your neural network using cleaned-up training data features from previous step
4. Testing your NN performance
Click on Model Testing > Classify All
5. Deploying your NN on WIO
•Click on Deployment
•Select Arduino library
•Build your Arduino library
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Copy contents from src directory into your project
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See implementation in EdgeImpulse folder
TinkerGen IDE
Machine Learning on TinkerGen IDE in WIO Terminal (Seeed Studio) to recognize shake and roll two die
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Navigate to TinkerGen IDE and create a free account.
Navigate to Model Creation and create a new model using accelerometer data.
•Start obtaining accelerometer data from WIO terminal for various labels by clicking on Data Acquisition. Note that the accelerometer data is collected for at least 2s which makes up 128 points (62.5Hz).
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Collect lots of data, more data is better. Yes, it takes time. Do not skip or skimp on this step
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Train your model using the collected data by clicking on Training and Deployment.
