Figure 8. Adding The Status Column; Figure 9. Creating Csv Files - ST AEKD-AICAR1 User Manual

• Add a status column for the car state for each specific acquisition (P = parking; N = normal; B = bumpy; S=
skid).
• Create a CSV file for each car state through a specific acquisition task.
• Merge all CSV files by coping and pasting each row without changing the time column values.
• Add a new dummy row at the end of the file with the time value equal to 100.
• Add random values for Ax, Ay, and Ax status.
Note: A ready-to-use dataset (Diff_profile.csv) has been created to train the network for the car state classification.
2.4.2.2 Neural network training with Google Colab
Import the training dataset contained in the CSV file into the Colab notebook environment. Then, run a parser
function on the imported data to build an input vector compliant with the LSTM RNN.
The following code block shows the Google Colab script, which imports and loads the CSV file.
from google.colab import files
uploaded = files.upload()
db = pd.read_csv('Diff_profile.csv',sep=',')
Parse each column of the CSV file (status, Acc_x, Acc_y, Acc_z, time).
UM3053 - Rev 1
Figure 8. Adding the status column
Figure 9. Creating CSV files
UM3053
AI-car sensing node life cycle
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