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Using Geospatial Information in Sensor Networks

John Heidemann and Nirupama Bulusu
USC/Information Sciences Institute

Abstract

This paper describes several ways sensor networks can benefit from geospatial information and identifies two research directions. First, better models of localization error, logical location, and communications costs are required to understand the interactions between spatial information and control and communications algorithms in sensor networks. Second, wider use of spatial information in densely deployed sensor networks will move sensor networking applications from simple tracking to object counting and area monitoring, and can enable the use of data mining techniques to sensor networks for ``spatial sensor mining''.

Availability

This paper is available in several formats: abstract web page with pointers and cites, gzip'ed postscript, PDF, paper copies can be obtained by mail to the authors. Copyright terms for this paper appear below.

Reference

Heidemann01d: John Heidemann and Nirupama Bulusu. Using Geospatial Information in Sensor Networks. In Proceedings of the Workshop on Intersections between Geospatial Information and Information Technology, Arlington, VA, USA, National Research Council. October, 2001. <http://www.isi.edu/~johnh/PAPERS/Heidemann01d.html>.

@inproceedings{Heidemann01d,
	author = "John Heidemann and Nirupama Bulusu",
	title = "Using Geospatial Information in Sensor Networks",
	booktitle = "Proceedings of the Workshop on Intersections between Geospatial Information and Information Technology",
	year = "2001",
	publisher = "National Research Council",
	address = "Arlington, VA, USA",
	month = "October",
	xxxpages = "no global page numbers",
	keywords = "localization, spatial sensor mining, xxx",
	url = "http://www.isi.edu/~johnh/PAPERS/Heidemann01d.html",
	pdfurl = "http://www.isi.edu/~johnh/PAPERS/Heidemann01d.pdf",
	psurl = "http://www.isi.edu/~johnh/PAPERS/Heidemann01d.ps.gz",
}

Copyright

This paper is copyright © 2001 by its authors. Permission to make digital or hard copies of part or all of this work for personal use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that new copies bear this notice and the full citation on the first page. Abstracting with credit is permitted.

To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission of the authors.