This material is based in part upon work supported by the National Science Foundation (NSF Terra-map) under Grant Number ___. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of NSF. NSF Program Director: Dr. Maria Zemankova.

Investigators: Naphtali D Rishe (FIU), Ouri Wolfson (IUC), Roberto Tamassia (Brown University), Maria I Cruz (UIC), Goce P Trajcevski (Northwestern University), Bo Xu (UIC), Tao Li (FIU), Scott Graham (FIU), Debra Davis (FIU)

Abstract

Florida International University, the University of Illinois at Chicago, Brown University, and Northwestern University are transforming the fields of computational transportation and mobile sensing by developing a universal high-performance model for information processing and fusion in mobile environment, providing a collaborative integration between the real and virtual worlds. This model enables querying and visualization of moving objects data (MOD) and their relationship to static and dynamic geospatial data. Expected results include: balancing the processing of location-based data streams 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 testbed at http://TerraFly.fiu.edu -- a public GIS mapping engine and location-based data repository.

This work takes a transformative step towards combining the real and virtual worlds, an emerging research frontier. The virtual world is relatively well understood, but this combination of the real and virtual poses great challenges and promises 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. By improving the efficiency of spatial, temporal, and moving object data management and making these results available to constituencies, the project is producing societal benefits. Student involvement at all levels, educational modules being developed, and curriculum expansion will have broad educational impacts. This project provides foundation for improving the quality of services in multiple applications such as disaster management, environmental monitoring, transportation, education, and logistics. The resulting technology will 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. Further information is available at the project's website, http://CAKE.fiu.edu/MOD.

Chicago Animated Driving Paths

Thumbnail links to TerraFly animations of trajectories supporting our Moving Objects Database Research: