The operation of smart subways brings data science and engineering together. In turn, smart metro stations based on holographic perception of the station, terminal platform control, and highly-autonomous operation, require expertise in both engineering and artificial intelligence. Smart Metro Station Systems introduces the key technologies of data science and engineering for smart metro station systems. The book consists in three main parts, focusing in turn on environment, people, and energy. Each chapter gives a series of practical applications. Having introduced smart metro stations, ten chapters present metro traffic flow monitoring and passenger guidance; methods for behavior analysis and trajectory projection; clustering and anomaly detection in crowd hotspots; monitoring and prediction for station humidity; monitoring and spatial prediction for air pollutants; time series feature extraction and analysis of metro load; characteristic and correlation analysis of metro load, and; prediction and intelligent ventilation control. This volume offers a key reference for an emerging area - smart metro stations - of use to those working on smart railways, data science, engineering, artificial intelligence, and aligned fields. Presents the core technologies of data science and engineering relevant to smart metro station systems Describes systems based on holographic perception, terminal platform control, and highly-autonomous operation Gives a large number of practical case studies and experimental designs Introduces state-of-the-art machine learning and data mining methods for smart metro station systems Offers a comprehensive and up-to-date research solution for the emerging area of smart metro stations
