Real-Time Capture, Management and Reconstruction of Spatio-Temporal Events

Richard Muntz* (PI)

William Jepson** (co-PI)

Sharad Mehrotra*** (co-PI)

Hanan Samet**** (co-PI)

Ouri Woulfson***** (co-PI)
* Computer Science Dept., UCLA

** Art and Architecture, UCLA

*** Information and Computer Science Dept., UC Irvine

**** Computer Science Dept., Univ. of Maryland

***** Computer Science Dept., Univ. of Ill., Chicago

Contact Information

Richard Muntz
4732 Boelter Hall

Computer Science Dept., UCLA
Los Angeles, CA 90095-1596
Phone: (310) 825-3546
Fax : (310) 825-2273
Email:

WWW PAGE

List of Supported Students and Staff (optional)

A total of 8 students and 2 staff/post-docs are supported on this grant.

Project Award Information

  • Award Number: IIS-0086116
  • Duration: 9/01 /2000 -- 8/31/2003
  • Title: Real-Time Capture, Management and Reconstruction of Spatio-Temporal Events

Keywords

Spatio-temporal databases, sensor rich environments, moving objects, multiresolution data, uncertain data, data visualization.

Project Summary

The objective of this research is to explore techniques for data collection, representation, indexing, and visualization of spatio-temporal information about the physical world and its phenomena. Specifically of interest is a new database architecture that integrates diverse sensors and/or actuators (that act as data generators) into a highly distributed dynamic distributed database. The proposal addresses fundamental issues of data collection, data representation, data replication, query processing and visualization in such environments. The proposal plans to demonstrate the techniques developed using a testbed of a smart transportation application.

Publications and Products

(Due to space limitations this is a much abbreviated list. See the project web page for a more complete list.)

Eamonn Keogh, Kaushik Chakrabarti, Michael Pazzani and Sharad Mehrotra "Locally Adaptive Dimensionality Reduction for Indexing Large Time Series Databases",
2001 ACM SIGMOD Conference on Management of Data, May, 2001.

Paul Castro, Richard Muntz, "Managing Context for Smart Spaces", IEEE
Personal Communications, October 2000.
B. Xu, O. Wolfson, S. Chamberlain,
"Spatially Distributed Databases on Sensors",
Proceedings of The 8th ACM Symposium on Advances in Geographic Information
Systems, Washington DC, Nov. 2000, pp. 153-160.

D. DeMenthon, P. David and H. Samet, ``Image to Model
Registration as a Fixed Point for Simultaneous Pose and Correspondence
Iterations'', submission to CVPR 2001, Kauai, December 11-13, 2001.

Project Impact

The integration of databases with an interactive visualization system developed at UCI is being being transferred to the Army Research Laboratory and integrated with their VGIS system for visualization of battlefield simulations. The localization system (Nibble) developed at UCLA is now in use at FX/PAL Laboratories and several universities. The DOMINO moving object database software developed at UIC is the basis for a recent commercial endeavor.

Goals, Objectives, and Targeted Activities

This is a recently started project. This first period has seen significant advances as indicated by research publications. This next year, in addition to continued work on individual research topics, the concentration will be on completion of the testbed system at UCLA and dissemination of the database collected.

Project References

See the project web page which can be accessed via

Area Background

While research on spatial and spatio-temporal databases has been an active research area for over two decades, especially in the context of geographical information systems, existing solutions exhibit severe limitation in the context of emerging sensor based applications. In particular, traditional approaches assume a centralized database where data can be organized on disk to facilitate efficient query and update processing. In the future environments envisioned, data will exist first and foremost at the locations that it is generated. Cost effectiveness will necessitate more in situ and distributed processing. Many other traditional topics in database mangement will have to be rethought. For example, the available data will depend on what type of sensors are available at the locale and at the time of interest. Data models and query processing will have to deal with uncertain and noisy data. Data coherence may be an issue due to the inability to obtain data at multiple locations at precisely the same time. Quality of responses in term of measures of accuracy become important due to uncertainly in the data available. Timeliness of responses or latency in triggers is another form of quality of service that is under investigation.

Area References

P. Saffo, “Sensors: The Next Wave of Infotech Inovation”, 1997,

P. Bonnet, J. Gehrke, P. Seshadri, “Querying the Physical World”, IEEE Personal Communications, Oct. 2000, pp.10-15.

T. Imielinski, S. Goel, “DataSpace: Querying and Monitoring Deeply Networked Collections in Physical Space”, IEEE Personal Communications, Oct. 2000, pp.4-9.