A survey on deep learning for human mobility

M Luca, G Barlacchi, B Lepri… - ACM Computing Surveys …, 2021‏ - dl.acm.org
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 …

Crime, inequality and public health: A survey of emerging trends in urban data science

M Luca, GM Campedelli, S Centellegher… - Frontiers in big …, 2023‏ - frontiersin.org
Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization
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

L Pappalardo, F Simini, G Barlacchi… - Journal of Statistical …, 2022‏ - jstatsoft.org
The last decade has witnessed the emergence of massive mobility datasets, such as tracks
generated by GPS devices, call detail records, and geo-tagged posts from social media …

Modelling taxi drivers' behaviour for the next destination prediction

A Rossi, G Barlacchi, M Bianchini… - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
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 …

Federated representation learning with data heterogeneity for human mobility prediction

X Zhang, Q Wang, Z Ye, H Ying… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
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 …

[HTML][HTML] Spatiotemporal patterns of human mobility and its association with land use types during COVID-19 in New York City

Y Jiang, X Huang, Z Li - ISPRS International Journal of Geo-Information, 2021‏ - mdpi.com
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 …

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 …

Influenza-like symptom recognition using mobile sensing and graph neural networks

G Dong, L Cai, D Datta, S Kumar, LE Barnes… - Proceedings of the …, 2021‏ - dl.acm.org
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 …

[PDF][PDF] Deep learning for human mobility: a survey on data and models

M Luca, G Barlacchi, B Lepri, L Pappalardo - arxiv preprint arxiv …, 2020‏ - iris.cnr.it
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 …

[HTML][HTML] Mobility and dissemination of COVID-19 in Portugal: correlations and estimates from Google's mobility data

N Mileu, NM Costa, EM Costa, A Alves - Data, 2022‏ - mdpi.com
The spread of the coronavirus disease 2019 (COVID-19) has important links with population
mobility. Social interaction is a known determinant of human-to-human transmission of …