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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao IEEE Intelligent Sys...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
IEEE Intelligent Systems
Article . 2015 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2015
Data sources: DBLP
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Precision Farming: Sensor Analytics

Authors: Stepan Ivanov; Kriti Bhargava; William Donnelly;

Precision Farming: Sensor Analytics

Abstract

The role of wireless sensor networks (WSNs) in agriculture has become prominent as part of the precision farming initiative. In the future, multiple WSN systems will be deployed on every farm. Accurate and timely analyses of the data collected by these systems will become paramount for increasing efficiency and sustainability of farming. Conventionally, analyzing monitoring data is considered to be beyond WSN capabilities, and, therefore, carried out remotely. Meanwhile, in recent years, complexity of the tasks performed by WSNs has been constantly increasing. Modern wireless sensors possess computational capacity sufficient for certain data-analytics functionality. This article overviews modern WSN functionality that incorporates a certain level of intelligence, while the authors explore challenges and potential benefits of WSN-based analytics in the scope of precision farming.

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    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).
    78
    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.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
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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!
78
Top 1%
Top 1%
Top 10%
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