Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
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 …
Human mobility data in the COVID-19 pandemic: characteristics, applications, and challenges
The COVID-19 pandemic poses unprecedented challenges around the world. Many studies
have applied mobility data to explore spatiotemporal trends over time, investigate …
have applied mobility data to explore spatiotemporal trends over time, investigate …
State-of-the-art deep learning: Evolving machine intelligence toward tomorrow's intelligent network traffic control systems
Currently, the network traffic control systems are mainly composed of the Internet core and
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
wired/wireless heterogeneous backbone networks. Recently, these packet-switched …
Machine learning for geographically differentiated climate change mitigation in urban areas
Artificial intelligence and machine learning are transforming scientific disciplines, but their
full potential for climate change mitigation remains elusive. Here, we conduct a systematic …
full potential for climate change mitigation remains elusive. Here, we conduct a systematic …
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 datasets, 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 …
Big data processing and analysis in internet of vehicles: architecture, taxonomy, and open research challenges
The extensive progression in the Internet of Vehicles (IoV) and the exponential upsurge in
data consumption reflect the importance of big data in IoV. In general, big data has gained a …
data consumption reflect the importance of big data in IoV. In general, big data has gained a …
Data-driven model predictive control of autonomous mobility-on-demand systems
The goal of this paper is to present an end-to-end, data-driven framework to control
Autonomous Mobility-on-Demand systems (AMoD, ie fleets of self-driving vehicles). We first …
Autonomous Mobility-on-Demand systems (AMoD, ie fleets of self-driving vehicles). We first …
Exploring trajectory prediction through machine learning methods
Human mobility prediction is of great importance in a wide range of modern applications in
different fields such as personalized recommendation systems, the fifth-generation (5G) …
different fields such as personalized recommendation systems, the fifth-generation (5G) …
Zooming into mobility to understand cities: A review of mobility-driven urban studies
Emerging big datasets about human mobility provide new and powerful ways of studying
cities and addressing various urban issues. However, human mobility has usually been …
cities and addressing various urban issues. However, human mobility has usually been …