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 organizations, government agencies, technology giants, and enterprizing 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 result in a broad range of indoor applications including emergency services, public services, in-store advertising, shopping, tracking, guided tours, and much more. In this tutorial, we first highlight the importance of indoor data management and the unique challenges that need to be addressed. Subsequently, we provide an overview of the existing research in indoor data management, covering modeling, cleansing, indexing, querying, and other relevant topics. Finally, we discuss the future research directions in this important and growing research area, discussing spatial-textual search, integrating outdoor and indoor spaces, uncertain indoor data, and indoor trajectory mining.
|Titel||32nd IEEE International Conference on Data Engineering, ICDE 2016, Helsinki, Finland, May 16-20, 2016|
|Forlag||IEEE Computer Society Press|
|Status||Udgivet - 2016|
|Begivenhed||32nd International Conference on Data Engineering (ICDE) - Helsinki, Finland|
Varighed: 16 maj 2016 → 20 maj 2016
|Konference||32nd International Conference on Data Engineering (ICDE)|
|Periode||16/05/2016 → 20/05/2016|