Distributed collaborative adaptive sensing for hazardous weather detection, tracking, and predicting

J. Brotzge, V. Chandresakar, K. Droegemeier, J. Kurose, D. McLaughlin, B. Philips, M. Preston, S. Sekelsky

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A new data-driven approach to atmospheric sensing and detecting/ predicting hazardous atmospheric phenomena is presented. Dense networks of small high-resolution radars are deployed with sufficient density to spatially resolve tornadoes and other dangerous storm events and overcome the earth curvature-induced blockage that limits today's ground-radar networks. A distributed computation infrastructure manages both the scanning of the radar beams and the flow of data processing by dynamically optimizing system resources in response to multiple, conflicting end-user needs. In this paper, we provide a high-level overview of a system architecture embodying this new approach towards sensing, detection and prediction. We describe the system's data rates, and overview various modes in which the system can operate.

Original languageEnglish (US)
Title of host publicationComputational Science — ICCS 2004
Subtitle of host publication4th International Conference, Kraków, Poland, June 6–9, 2004, Proceedings, Part III
EditorsMarian Bubak, Geert Dick van Albada, Peter M. A. Sloot, Jack J. Dongarra
PublisherSpringer
Pages670-677
Number of pages8
ISBN (Print)3540221166
DOIs
StatePublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science
Volume3038
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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