Researchers at Florida International University (IIS-1213026), University of Illinois at Chicago (IIS-1213013), Brown University (IIS-1212508), and Northwestern University (IIS-1213038) are developing a high-performance model for information processing and fusion in mobile environments, providing a collaborative integration between the real and virtual worlds. This model, applicable to the fields of computational transportation and mobile sensing, enables querying and visualization of moving objects data (MOD) and their relationship to static and dynamic geospatial data. Research project addresses the issues of: balancing the processing of location-based data streams coming into MOD servers with efficient processing of visualization-related queries; determining optimal distribution of queries/tasks among multiple regional servers; maximizing the scalability of prediction techniques in terms of efficient management of objects' data and queries; modeling data uncertainty; coupling map generalization with trajectories' data reduction when zooming across different scales; resolving issues of privacy and security; and enabling semantic querying. A demonstration of the outcomes is available within the TerraFly testbed (http://TerraFly.fiu.edu) -- a public Geographic Information System (GIS) mapping engine and location-based data repository.This work explores the novel steps towards combining the real and virtual worlds, an emerging research frontier. The virtual world is relatively well understood, but the combination of the real and virtual poses great challenges and promises transformative results with high potential payoff, including in-car navigation systems, massive fleets of mobile sensors, self-navigating vehicles, situation command, and location-based services. While advancing Computer Science, the project also leverages prior investment of, and provides direct benefit to, NSF, NASA, DoI, DoT, DHS, and other stakeholders such as the NSF EarthCube project. By improving the efficiency of spatial, temporal, and moving object data management and making these results available to constituencies via TerraFly, EarthCube and other venues, the project will produce societal benefits. This project provides a foundation for improving the quality of services in multiple applications such as disaster management, environmental monitoring, transportation, education, and logistics. The resulting technologies may serve as a base to advance research on self-navigating vehicles, robots, and mobile sensors. In particular, this work facilitates the technologies of Informed Traveler Programs, dynamic navigation, situation control, and airborne observational systems. The project provides rich educational and research opportunities for students from the collaborating institutions -- including underrepresented students. In addition, educational modules are developed, and research results will be incorporated in curriculum expansions. Further information is available at the project's website (http://CAKE.fiu.edu/MOD).
