Modelling the movement uncertainty of crowdsourced human trajectories in complex urban
areas is useful for various human mobility analytics and applications. However, the existing …

Modelling pedestrian movement uncertainty in complex urban environments is regarded as
a meaningful and challenging task regarding the promotion of geospatial data mining and …

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

With the continued deployment of the Internet of Things (IoT), increasing volumes of devices
are being deployed that emit massive spatially referenced data. Due in part to the dynamic …

Indoor venues accommodate many people who collectively form crowds. Such crowds in
turn influence people's routing choices, eg, people may prefer to avoid crowded rooms when …

WiFi fingerprint-based indoor positioning system emerges to provide fundamental location-
related service in heterogeneous communications networks. It relies on crowdsourcing …

Accurate and robust indoor location prediction plays an important role in indoor location
services. Markov chains (MCs) have been widely adopted for location prediction due to their …

Pandemics often cause dramatic losses of human lives and impact our societies in many
aspects such as public health, tourism, and economy. To contain the spread of an epidemic …

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

Indoor shortest path query (ISPQ) is of fundamental importance for indoor location-based
services (LBS). However, existing ISPQs ignore indoor temporal variations, eg, the open and …