Making Sense of Trajectory Data: A Database Approach (2011–2013)

Trajectory data records the time and positions of moving objects such as vehicles, people and animals. Wide availability of trajectory data due to the proliferation of GPS-enabled mobile devices, combined with easy access to digital maps and emerging computing platforms such as cloud computing, makes many novel data-driven, location-based applications possible. Existing data management technologies, however, cannot properly handle trajectory data due to their sheer volume, high complexity and streaming nature. This project aims at addressing key issues in providing efficient and effective ways of capturing, storing, searching and analysing large scale trajectory data in a database approach.
Grant type:
ARC Discovery Projects
  • Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council