Indoor Data Management

A large part of modern life is lived indoors such as in homes, offices, shopping malls, universities, libraries and airports. However, almost all of the existing location-based services (LBS) have been designed only for outdoor space. This is mainly because the global positioning system (GPS) and other positioning technologies cannot accurately identify the locations in indoor venues. Some recent initiatives have started to cross this technical barrier, promising huge future opportunities for research organisations, government agencies, technology giants, and enterprising start-ups -- to exploit the potential of indoor LBS. Consequently, indoor data management has gained significant research attention in the past few years and the research interest is expected to surge in the upcoming years. This will results in a broad range of indoor applications including emergency services, public services, in-store advertising, shopping, tracking, guided tours, and much more. In this project, we are interested in developing efficient query processing techniques for indoor location data considering textual keywords associated with objects, and data uncertainty.