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Coordinated inland area Search and Rescue (SAR) planning and execution tool

Authors: Castle, Timothy S.;

Coordinated inland area Search and Rescue (SAR) planning and execution tool

Abstract

This thesis designs and implements the Coordinated Inland Area Search and Rescue (SAR) System (COINSS). This n provides several important features not provided by current inland SAR computer systems. First is the ability to model movement of the target. Second is modeling the effect terrain has on the movement of the target. Third is the visual presentation of a probability map, a color display showing the probability that the target is located at various geographic positions. COINSS is developed in the Java programming language. It is designed to be implemented with a map-based planning system using loosely coupled components. COINSS provides the initialization, movement, and search algorithms which are used by the planning system to support the search operation. The initialization algorithms define the search area where the SAR operation wil occur. Initial areas are defined for the target. COINSS models the movement of the target as a discrete time Markov chain. Bayes theorem is used to update the probability map when negative search information is provided. This thesis will improve inland SAR operations by providing the first model with an interactive graphical user interface and a model of target movement

Approved for public release; distribution is unlimited.

http://archive.org/details/coordinatedinlan109458156

Lieutenant, United States Coast Guard

Keywords

Map Based Planning, Loosely Coupled Components, Search and Rescue, Java

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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