Intelligent system for predicting wireless sensor network performance in on-demand deployments. Otero, C.; Kostanic, I.; Peter, A.; Ejnioui, A.; and Daniel Otero, L. In 2012 IEEE Conference on Open Systems, ICOS 2012, 2012.
abstract   bibtex   
The need for advanced tools that provide efficient design and planning of on-demand deployment of wireless sensor networks (WSN) is critical for meeting our nation's demand for increased intelligence, reconnaissance, and surveillance in numerous safety-critical applications. For practical applications, WSN deployments can be time-consuming and error-prone, since they have the utmost challenge of guaranteeing connectivity and proper area coverage upon deployment. This creates an unmet demand for decision-support systems that help manage this complex process. This paper presents research-in-progress to develop an advanced decision-support system for predicting the optimal deployment of wireless sensor nodes within an area of interest. The proposed research will have significant impact on the future application of WSN technology, specifically in the emergency response, environmental quality, national security, and engineering education domains. © 2012 IEEE.
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 title = {Intelligent system for predicting wireless sensor network performance in on-demand deployments},
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 year = {2012},
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 keywords = {[deployments, image processing, machine learning,},
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 abstract = {The need for advanced tools that provide efficient design and planning of on-demand deployment of wireless sensor networks (WSN) is critical for meeting our nation's demand for increased intelligence, reconnaissance, and surveillance in numerous safety-critical applications. For practical applications, WSN deployments can be time-consuming and error-prone, since they have the utmost challenge of guaranteeing connectivity and proper area coverage upon deployment. This creates an unmet demand for decision-support systems that help manage this complex process. This paper presents research-in-progress to develop an advanced decision-support system for predicting the optimal deployment of wireless sensor nodes within an area of interest. The proposed research will have significant impact on the future application of WSN technology, specifically in the emergency response, environmental quality, national security, and engineering education domains. © 2012 IEEE.},
 bibtype = {inProceedings},
 author = {Otero, C.E. and Kostanic, I. and Peter, A. and Ejnioui, A. and Daniel Otero, L.},
 booktitle = {2012 IEEE Conference on Open Systems, ICOS 2012}
}
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