Individuals' indoor trajectories can be reconstructed with sensing data for indoor navigation.
However, the movement uncertainty of such reconstructed indoor trajectories has seldom …

As people spend significant parts of daily lives indoors, it is useful and important to measure
indoor densities and find the dense regions in many indoor scenarios like space …

Trajectory frequent pattern mining is an important branch of data mining. The constraint of
indoor space is between Euclid space and road network space, which makes it difficult to …

In recent years, technologies of indoor crowd positioning and movement data analysis have
received widespread attention in the fields of reliability management, indoor navigation, and …

Monitoring and assistive technologies (MATs) are being used more frequently in healthcare.
A central ethical concern is the compatibility of these systems with the moral preferences of …

Knowing popular indoor locations can benefit many applications like exhibition planning
and location-based advertising, among others. In this work, we use uncertain historical …

With the wide availability of low-cost proximity sensors, a large body of research focuses on
digital person-to-person contact tracing applications that use proximity sensors. In most …

In applications such as elderly care, dementia anti-wandering and pandemic control, it is
important to ensure that people are within a predefined area for their safety and well-being …

Real‐time mobile crowd‐sourcing data often available in indoor and outdoor environments
offer many opportunities for the analysis of human trajectories. However, this stresses the …

The growing ubiquity of location/activity sensing technologies has created unprecedented
opportunities for research on human spatiotemporal interaction behavior in mobile …