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: muntz@cs.ucla.edu
WWW PAGE
http://mmsl.cs.ucla.edu
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 http://mmsl.cs.ucla.edu.
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,
http://www.saffo.org/sensors.html
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.