In the past few years the data capturing aspects of human mobility become widely available in the real world, e.g., mobile phone records, GPS traces of vehicles and pedestrians, ticketing logs of public transportation, geo-tagged Web objects (such as online check-ins, geo-tagged photos and videos), as well as records from roadside sensor networks. This has given a new empirically driven momentum to the human mobility computing as an emerging concept. Far beyond statistical analytics of human motion history, human mobility computing aims to acquire more insightful knowledge by integrating a variety of heterogeneous data sources and applying a range of techniques in multiple disciplines such as computer science, Anthropology, social science, and physics. As a result, we can gain deeper understanding on many aspects of human daily life, including the activities, behaviours, habits, preferences, lifestyles and intentions. On top of that, we have better chance to develop effective strategies and build intelligent systems that play critical roles in areas like public health, traffic engineering, urban planning and economic forecasting.

This workshop provides the professionals, researchers, engineers and practitioners who are interested in acquiring, managing, mining and understanding human mobility with a platform where they can discuss issues and challenges, share the state-of-the-art of the development and applications, present their ideas and contributions, and set future directions in emerging innovative research for human mobility computing.

Topics of interest include, but not limited to, the following aspects:

New platforms and applications for sensing and acquiring human mobility data
Integration of heterogeneous human mobility data sources
Theoretic and/or empirical modelling of human mobility data
Discovery of human mobility patterns (e.g., anomaly, event, etc.)
Data quality and uncertainty issues study on human mobility data
Efficient indexing and processing for large scale vehicle/pedestrian trajectories
Activity and behaviour mining from human mobility data
Social behaviour analysis on location-based social networks
Semantic annotation and tagging for human moving trajectories
Intelligent POI recommendation system
Real-time analysis for streaming trajectory data
Human mobility data compression
Human mobility computing in the Cloud
Privacy issues in human mobility data