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 …

scikit-mobility: A Python library for the analysis, generation and risk assessment of mobility data

L Pappalardo, F Simini, G Barlacchi… - arXiv preprint arXiv …, 2019 - arxiv.org
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 …

Using big data to study the link between human mobility and socio-economic development

L Pappalardo, D Pedreschi, Z Smoreda… - … conference on big …, 2015 - ieeexplore.ieee.org
Big Data offer nowadays the potential capability of creating a digital nervous system of our
society, enabling the measurement, monitoring and prediction of relevant aspects of socio …

Data-driven generation of spatio-temporal routines in human mobility

L Pappalardo, F Simini - Data Mining and Knowledge Discovery, 2018 - Springer
The generation of realistic spatio-temporal trajectories of human mobility is of fundamental
importance in a wide range of applications, such as the developing of protocols for mobile …

An analytical framework to nowcast well-being using mobile phone data

L Pappalardo, M Vanhoof, L Gabrielli… - International Journal of …, 2016 - Springer
An intriguing open question is whether measurements derived from Big Data recording
human activities can yield high-fidelity proxies of socio-economic development and well …

[HTML][HTML] Graph-based mobility profiling

H Martin, N Wiedemann, DJ Reck, M Raubal - Computers, Environment and …, 2023 - Elsevier
The decarbonization of the transport system requires a better understanding of human
mobility behavior to optimally plan and evaluate sustainable transport options (such as …

[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 …

Gravity and scaling laws of city to city migration

R Prieto Curiel, L Pappalardo, L Gabrielli, SR Bishop - PloS one, 2018 - journals.plos.org
Models of human migration provide powerful tools to forecast the flow of migrants, measure
the impact of a policy, determine the cost of physical and political frictions and more. Here …

[PDF][PDF] Generating mobility networks with generative adversarial networks

G Mauro, M Luca, A Longa, B Lepri, L Pappalardo - EPJ data science, 2022 - Springer
The increasingly crucial role of human displacements in complex societal phenomena, such
as traffic congestion, segregation, and the diffusion of epidemics, is attracting the interest of …

Deep activity model: A generative approach for human mobility pattern synthesis

X Liao, Q Jiang, BY He, Y Liu, C Kuai, J Ma - arXiv preprint arXiv …, 2024 - arxiv.org
Human mobility plays a crucial role in transportation, urban planning, and public health.
Advances in deep learning and the availability of diverse mobility data have transformed …