MetroPT data set

The MetroPT data set is an outcome of a eXplainable Predictive Maintenance (XPM) project with an urban metro public transportation service in Porto, Portugal. The data was collected during 2022 that aimed to develop machine learning methods for online anomaly detection and failure prediction. By capturing several analogic sensor signals (pressure, temperature, current consumption), digital signals (control signals, discrete signals), and GPS information (latitude, longitude, and speed), we provide a framework that can be easily used and developed for the new machine learning methods. We believe this dataset contains some interesting characteristics and can be a good benchmark for predictive maintenance models.

The dataset is available on the zenodo platform: https://doi.org/10.5281/zenodo.6854240

The description of the dataset is now available online: https://doi.org/10.1038/s41597-022-01877-3