ACM Home Page
Please provide us with feedback. Feedback
Using tomography for ubiquitous sensing
Full text PdfPdf (436 KB)
Source
Geographic Information Systems archive
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems table of contents
Irvine, California
SESSION: Geo sensing table of contents
Article No. 5  
Year of Publication: 2008
ISBN:978-1-60558-323-5
Authors
Stacy Patterson  University of California, Santa Barbara, CA
Bassam Bamieh  University of California, Santa Barbara, CA
Amr El Abbadi  University of California, Santa Barbara, CA
Sponsors
: Google
: Oak Ridge National Laboratory
: ESRI
Microsoft : Microsoft
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 10,   Downloads (12 Months): 127,   Citation Count: 0
Additional Information:

abstract   references   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1463434.1463441
What is a DOI?

ABSTRACT

By embedding sensors in mobile devices, it is possible to exploit the ubiquitous presence of these devices to construct applications for large-scale sensing and monitoring of environmental phenomena. To this end, we present Environmental Tomography, a novel approach in which mobile devices participate in the collection of aggregate sensor readings along roads or sidewalks, and these aggregates are used to reconstruct an estimate of the contaminant distribution throughout a region. We demonstrate how our data collection process preserves user location privacy and is robust to sensor and location reading errors. We also show how the estimation process can be formulated as a convex optimization problem that incorporates the physical dynamics of the phenomenon of interest. We study the performance of Environmental Tomography using various road network layouts and realistic models of pollution. Results indicate that estimates generated from path aggregates are of comparable accuracy to estimates generated from significantly greater numbers of individual sensor readings.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1
 
2
 
3
A. Capone, L. Pizziniaco, I. Filippini, and M. de la Fuente. A sift: an efficient method for trajectory based forwarding. In 2nd International Symposium on Wireless Communication Systems (ISWCS), pages 135--139, 2005.
 
4
R. Castro, M. Coates, G. Liang, R. Nowak, and B. Yu. Network tomography: Recent developments. Statistical Science, 19(3):499--517, 2004.
 
5
cvx: Matlab software for disciplined convex programming. http://www.stanford.edu/boyd/cvx/, 2007. {Online; accessed 28-October-2007}.
 
6
EPA technology transfer network, support center for regulatory atmospheric modeling. http://www.epa.gov/scram001/dispersionindex.htm. {Online; accessed 01-June-2008}.
 
7
Equator. http://www.equator.ac.uk. {Online; accessed 01-June-2008}.
 
8
S. J. Farlow. Partial Differential Equations for Scientists and Engineers (Dover Books on Advanced Mathematics). General Publishing Company, Ltd., 1993.
9
 
10
11
12
 
13
E. Lawrence, G. Michailidis, V. N. Nair, and B. Xi. Frontiers in Statistics, chapter Network Tomography: A Review and Recent Developments. Imperial College Press, July 2005.
 
14
W. Menke. Geophysical Data Analysis: Discrete Inverse Theory, volume 45 of International Geophysics Series. Academic Press, Inc., 1989.
 
15
16
17
 
18
Participatory urbanism. http://www.urban-atmospheres.net/ParticipatoryUrbanism/index.html. {Online; accessed 01-June-2008}.
 
19
F. Pasquill. Atmospheric Diffusion. Wiley, New York, 1974.
 
20
S. Patterson, B. Bamieh, and A. El Abbadi. Environmental tomography: Ubiquitous sensing with mobile devices. In Proceedings of the IEEE 24th International Conference on Data Engineering (ICDE) (demonstration), pages 1560--1563, 2008.
 
21
 
22
SDPT3 version 4.0 (beta) - a matlab software for semidefinite-quadratic-linear programming. http://www.math.nus.edu.sg/mattohkc/sdpt3.html/, 2007. {Online; accessed 28-October-2007}.
 
23
Senseweb. http://research.microsoft.com/nec/senseweb/. {Online; accessed 01-June-2008}.
 
24
Sensor planet. http://www.sensorplanet.org. {Online; accessed 01-June-2008}.
 
25
I. Stojmenovic. Position-based routing in ad hoc networks. IEEE Communications Magazine, 40(7):128--134, July 2002.
 
26
O. Sutton. Micrometeorology: A Study of Physical Processes in the Lowest Layers of the Earth's Atmosphere. McGraw-Hill, New York, 1953.
 
27
Urban sensing. http://research.cens.ucla.edu/projects/2006/Systems/Urban Sensing/default.htm. {Online; accessed 01-June-2008}.
 
28
M. Yuksel, R. Pradhan, and S. Kalyanaraman. An implementation framework for trajectory-based routing in ad hoc networks. Ad Hoc Networks, 4(1):125--137, January 2006.

Collaborative Colleagues:
Stacy Patterson: colleagues
Bassam Bamieh: colleagues
Amr El Abbadi: colleagues