A survey on deep learning for human mobility
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …
such as disease spreading, urban planning, well-being, pollution, and more. The …
[HTML][HTML] Crime, inequality and public health: a survey of emerging trends in urban data science
Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization
and increasing urbanization posing new challenges in sustainable urban development well …
and increasing urbanization posing new challenges in sustainable urban development well …
scikit-mobility: A Python library for the analysis, generation and risk assessment of mobility data
The last decade has witnessed the emergence of massive mobility data sets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …
generated by GPS devices, call detail records, and geo-tagged posts from social media …
Modelling taxi drivers' behaviour for the next destination prediction
In this paper, we study how to model taxi drivers' behavior and geographical information for
an interesting and challenging task: the next destination prediction in a taxi journey …
an interesting and challenging task: the next destination prediction in a taxi journey …
[PDF][PDF] Deep learning for human mobility: a survey on data and models
Urban population is increasing strikingly and human mobility is becoming more complex
and bulky, affecting crucial aspects of people lives such as the spreading of viral diseases …
and bulky, affecting crucial aspects of people lives such as the spreading of viral diseases …
[HTML][HTML] Spatiotemporal patterns of human mobility and its association with land use types during COVID-19 in New York City
The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society.
One of the non-pharmacological measures to contain the COVID-19 infection is social …
One of the non-pharmacological measures to contain the COVID-19 infection is social …
Federated representation learning with data heterogeneity for human mobility prediction
The advancement of smart wearable devices and location-based smart services has
enabled a new paradigm for smart human mobility prediction (HMP), which has a broad …
enabled a new paradigm for smart human mobility prediction (HMP), which has a broad …
Using autoencoders to automatically extract mobility features for predicting depressive states
A Mehrotra, M Musolesi - Proceedings of the ACM on Interactive, Mobile …, 2018 - dl.acm.org
Recent studies have shown the potential of exploiting GPS data for passively inferring
people's mental health conditions. However, feature extraction for characterizing human …
people's mental health conditions. However, feature extraction for characterizing human …
Influenza-like symptom recognition using mobile sensing and graph neural networks
Early detection of influenza-like symptoms can prevent widespread flu viruses and enable
timely treatments, particularly in the post-pandemic era. Mobile sensing leverages an …
timely treatments, particularly in the post-pandemic era. Mobile sensing leverages an …
[HTML][HTML] Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: A cross-sectional study using GPS from 122 individuals in three …
Many aspects of our life are related to our mobility patterns and individuals can exhibit
strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in …
strong tendencies towards routine in their daily lives. Intrapersonal day-to-day variability in …