PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Updating and Querying Databases that Track Mobile Units
Distributed and Parallel Databases - Special issue on mobile data management and applications
Indexing moving points (extended abstract)
PODS '00 Proceedings of the nineteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A data model and data structures for moving objects databases
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Indexing the positions of continuously moving objects
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)
Using space-time grid for efficient management of moving objects
Proceedings of the 2nd ACM international workshop on Data engineering for wireless and mobile access
Modeling and Querying Moving Objects
ICDE '97 Proceedings of the Thirteenth International Conference on Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Moving Objects Databases: Issues and Solutions
SSDBM '98 Proceedings of the 10th International Conference on Scientific and Statistical Database Management
A Spatiotemporal Model and Language for Moving Objects on Road Networks
SSTD '01 Proceedings of the 7th International Symposium on Advances in Spatial and Temporal Databases
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Recently much research has been done in applying database technology to tracking moving objects. Most techniques assume a predictable linear motion. We present a new application for moving object databases, characterized by repetitive, unpredictable motion with very high data rates. In particular, the domain of athletic and auto races is presented. We found existing moving object methods do not adequately address this application area. A data model is presented for efficiently storing the data. A spatiotemporal index is developed for fast retrieval of data. We give a set of queries likely to be of interest in this application domain. A study is presented showing our implementation has better performance than those based on relational DBMSs.