Last update: September 2014

SemanticMOVE Framework

Moving objects of different types (mobile users with mobile devices, cars, other vehicles, etc.) play a key role in smart cities. The efficient management of information provided and used by these moving entities (including their location, trajectories, features, etc.) allows to understand and analyze how cities are performing and to provide contextual and adapted services to citizens, such as traffic management, urban dynamics analysis, ambient assisted living, emergency management, m-health, etc. Whereas significant effort has been invested in the modeling of moving objects and some steps have been performed regarding the representation of certain semantics associated to them (semantic locations and semantic trajectories, as opposed to purely geographic locations), further efforts are needed for a full-fledged semantic management of moving objects that can be efficiently and flexibly exploited in smart cities. By mixing methods and techniques developed in different fields like moving object databases and the Semantic Web, it is possible to enhance the way information about moving objects is managed (from the modeling, querying, processing, and analysis points of view). n our ongoing joint work, we are defining a generic and scalable distributed framework (SemanticMOVE) whose realization would enable a comprehensive management of the semantics of moving objects that would leverage the increasing sensing, processing, interaction, and communication capabilities of mobile devices in a scalable and effective way. As opposed to other related work, we envision a quite generic architecture, supporting a fully distributed and interoperable scenario for the management of semantics of moving objects. In this web page, we will provide up-to-date information about the development of our framework.

Research team

The following persons are currently jointly working on the definition of this framework:

Most Related Publications

Acknowledgements

This work is partially supported by: The authors acknowledge the support of the European COST Action IC0903 MOVE, that fosters research collaboration in this field.



University of Zaragoza
University of Nis
IRENav