Digital sources have been enabling unprecedented data-driven and large-scale
investigations across a wide range of domains, including demography, sociology …

Understanding crowd mobility is critical for many applications. In this paper, we propose
CrowdMirage, a WiFi positioning-based crowd mobility digital twin for smart campuses …

Urban land usage recognition (ULUR) in smart urban sensing recognizes the physical
attributes and socioeconomic functions of urban land resources using pervasive satellite …

The scarcity of publicly available cellular association traces hinders user location-based
research and various data-driven services, highlighting the importance of data synthesis in …

The map matching of cellular data reconstructs real trajectories of users by exploiting the
sequential connections between mobile devices and cell towers. The difficulty in obtaining …

Location-based Behavioral Analytics (LBA) holds a great potential for improving the services
available in smart cities. Naively implemented, such an approach would track the …

Obtaining urban-scale vehicle trajectories is essential to understand urban mobility and
benefits various downstream applications. The mobility knowledge obtained from existing …

Human mobility trajectories are fundamental resources for analyzing mobile behaviors in
urban computing applications. However, these trajectories, typically collected from location …

The context about trips and users from mobility data is valuable for mobile service providers
to understand their customers and improve their services. Existing inference methods …

Human mobility models typically produce mobility data to capture human mobility patterns
individually or collectively based on real-world observations or assumptions, which are …