SAC '98 Proceedings of the 1998 ACM symposium on Applied Computing
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)
ACM Computing Surveys (CSUR)
R-trees: a dynamic index structure for spatial searching
SIGMOD '84 Proceedings of the 1984 ACM SIGMOD international conference on Management of data
On R-trees with low query complexity
Computational Geometry: Theory and Applications
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
MV3R-Tree: A Spatio-Temporal Access Method for Timestamp and Interval Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Hilbert R-tree: An Improved R-tree using Fractals
VLDB '94 Proceedings of the 20th 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
Research in mobile database query optimization and processing
Mobile Information Systems
Data retrieval for location-dependent queries in a multi-cell wireless environment
Mobile Information Systems
The TPR*-tree: an optimized spatio-temporal access method for predictive queries
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Spatio-Temporal Indexing for Large Multimedia Applications
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Similarity measures for trajectory of moving objects in cellular space
Proceedings of the 2009 ACM symposium on Applied Computing
Indexing the Trajectories of Moving Objects in Symbolic Indoor Space
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Monitoring Orientation of Moving Objects around Focal Points
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
Cognitive Techniques in Visual Data Interpretation
Cognitive Techniques in Visual Data Interpretation
Supporting Continuous Range Queries in Indoor Space
MDM '10 Proceedings of the 2010 Eleventh International Conference on Mobile Data Management
RFID-based human behavior modeling and anomaly detection for elderly care
Mobile Information Systems
CISIS '11 Proceedings of the 2011 International Conference on Complex, Intelligent, and Software Intensive Systems
A new trajectory indexing scheme for moving objects on road networks
BNCOD'06 Proceedings of the 23rd British National Conference on Databases, conference on Flexible and Efficient Information Handling
A method for identification of moving objects by integrative use of a camera and accelerometers
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Multi-camera tracking using a Multi-Goal Social Force Model
Neurocomputing
Indexing Moving Objects in Indoor Cellular Space
NBIS '12 Proceedings of the 2012 15th International Conference on Network-Based Information Systems
Indexing moving objects for directions and velocities queries
Information Systems Frontiers
Indexing of Spatiotemporal Objects in Indoor Environments
AINA '13 Proceedings of the 2013 IEEE 27th International Conference on Advanced Information Networking and Applications
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To facilitate a variety of indoor applications, positioning technologies have been developed in indoor spaces (such as WI-FI and RFID). Thus, the requirement for the tracking and monitoring of moving objects in indoor spaces has increased considerably. The indexing of moving objects in indoor spaces is of essential importance, as these are different from outdoor spaces in many respects, such as the measurements and the positioning technologies. Therefore, in this paper, we propose a new adjacency-index structure for objects moving in indoor space which includes both spatial and temporal properties. The spatial index is based on the connectivity (adjacency) between the indoor environment cells. Moreover, we propose two temporal indexes with different methods to store the temporal data, which can support and enable efficient query processing and efficient updates for objects moving in indoor space. The proposed indexes can efficiently serve different types of spatial queries, such as KNN and indoor range, and a variety of temporal queries which are essential in an indoor environment. An empirical performance study suggests that the proposed data structures are effective, efficient, and robust.