This first section introduces the topic presented and the related state-of-theart developments. Time series data mining (TSDM) mainly consists of the following tasks: anomaly detection (Blázquez-García et al., 2020), classification (Ismail-Fawaz et al., 2019), analysis and preprocessing (Hamilton, 1994), segmentation (Keogh et al., 2004), clustering (Liao, 2005) and prediction (Weigend, 2018). More concretely, this chapter is focused on the applications of time series preprocessing, segmentation and prediction to real-world problems.