In this use case specifically, Shapelets helps in executing a comparison of anomaly detectionmodels from different libraries or frameworks and producing and integrated benchmark with the purpose of selecting the best solution.
As a result, this data app allows us to present an accurate predictive maintenance plan to detect anomalies in the sensor data to prevent machinery failures.
Consequently, this use case serves as a starting point to develop a solution that can be used to detect anomalies in an online setup. It presents a suitable anomaly detection method to obtain reasonable performance, given the little and uncontextualized data available, which are simply temperature values.
Now it’s your turn to use this study to develop you own solution. What are you waiting for?