This method describes an analytical framework to nowcast well-being by using mobility measures extracted from mobile phone data.

In the last decade, the number of studies about machine learning algorithms applied to sports, e.g., injury forecasting and athlete performance prediction, have rapidly...

The standard deviation of the interval between QRS complexes recorded over 24 h (SDNN24) is an important metric of cardiovascular health. Wrist-worn fitness wearable devices...

The use of machine learning (ML) in soccer allows for the management of a large amount of data deriving from the monitoring of sessions and matches. Although the rate of...

Wrist-worn wearable devices equipped with heart rate (HR) sensors have become increasingly popular. The ability to correctly interpret the collected data is fundamental to...

Geolet is a Python library that offers an interpretable transformation and classification approach for trajectory data. Geolet first partitions trajectories into multiple...

An event classification package.

Non-Pharmaceutical Interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, have dramatically influenced our everyday behaviour. This method allows to...

The increasingly crucial role of human displacements in complex societal phenomena, such as traffic congestion, segregation, and the diffusion of epidemics, is attracting the...

The non-pharmaceutical interventions (NPIs), aimed at reducing the diffusion of the COVID-19 pandemic, has dramatically influenced our behaviour in everyday life. We developed...

A collection of methods (relying on the scikit-mobility and OSMnx Python libraries) to compute emissions starting from vehicles' mobility trajectories. In particular, methods...

This method provides a Privacy Risk Assessment on mobility data, in terms of trajectories or aggregation of trajectories, i.e., locations with frequency of visit and locations...

This course is an introduction to data collection, data preparation & transformation and data analysis. It contains the essential concepts for a researcher in order to...

We used the mobility-emission methods (https://data.d4science.org/ctlg/ResourceCatalogue/mobility-emissions) to perform experiments on real GPS trajectories describing 433,272...

In this experiment we simulate the mobility of individuals in New York City, London, and Tokyo, using STS-EPR. For each city, we compare the synthetic trajectories generated...

Soccer & Data Cup at Expo Dubai 2020 will be a 3-days international hybrid marathon of Sport Analytics combining fundamental techniques of data analysis and Artificial...

The aim of this study was to investigate whether volleyball-specific skills, physical performance, and general cognitive functions differ between players of different...

Scikit-mobility is a library for human mobility analysis in Python. The library allows to: represent trajectories and mobility flows with proper data structures, TrajDataFrame...