A data model and data structures for moving objects databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A foundation for representing and querying moving objects
ACM Transactions on Database Systems (TODS)
Spatial SQL: A Query and Presentation Language
IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering
Capturing the Uncertainty of Moving-Object Representations
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
Evaluating probabilistic queries over imprecise data
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Managing uncertainty in moving objects databases
ACM Transactions on Database Systems (TODS)
Querying Imprecise Data in Moving Object Environments
IEEE Transactions on Knowledge and Data Engineering
Modeling historical and future movements of spatio-temporal objects in moving objects databases
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
A Hybrid Prediction Model for Moving Objects
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Uncertain Range Queries for Necklaces
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
Path prediction and predictive range querying in road network databases
The VLDB Journal — The International Journal on Very Large Data Bases
Probabilistic range queries for uncertain trajectories on road networks
Proceedings of the 14th International Conference on Extending Database Technology
Querying moving objects with uncertainty in spatio-temporal databases
DASFAA'11 Proceedings of the 16th international conference on Database systems for advanced applications - Volume Part I
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The spatio-temporal uncertainty is an inherent feature of moving objects. One scenario where uncertainty exists is the movement of moving objects in the future, which results from lacking the knowledge of the prediction method. To solve this problem is useful, for example, to predict the locations of a hurricane and its relationships with points of interest on the land. The solution calls for a sound model to describe and handle the uncertainty properly. This paper introduces such a model which represents the spatio-temporal uncertainty in the near future. We introduce an uncertainty model called the balloon model specifically for future movements. We discuss how to implement the balloon model in the moving object database and define some important operations on querying the uncertainty.