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Difficult is that, in most cases, there are no labels for the data, and primarily, only normal behavior data with sporadic error cases are available. Clustering, unsupervised, one-class classification, and anomaly detection approaches appear promising. This survey paper explores the application of unsupervised deep learning techniques in sensor data collected from trucks. 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