Hands-On Industrial Internet of Things

Step 3 – building the model

As mentioned previously, one of the problems of the proposed algorithm is the lack of information about the dataset—we do not know the normal operation of the airplane. For this reason, we have implemented a simple method that identifies when a data point falls outside the standard deviation.

We can improve our algorithm using an unsupervised ML algorithm. A particularly interesting algorithm is the One-Class Support Vector Machine (OCSVM). The OCSVM splits data points into two different classes—good or bad. It requires a training dataset to build the boundaries. We can use the full dataset for the training phase and then evaluate each point to see if it falls into the good class or not. Our dataset has to be normalized, ...