Interactive Visual Big Data Analytics for Large Area Farm Biosecurity Monitoring: i-EKbase System

Ritaban Dutta, Heiko Mueller, Daniel Smith, Aruneema Das, Jagannath Aryal
Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, PMLR 41:9-18, 2015.

Abstract

In this industrial application paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. We propose a cloud computing based intelligent big data analysis and interactive visual analytics platform to predict farm hot spots with high probability of potential biosecurity threats and early monitoring system aiming to save the farm from significant economic damage.

Cite this Paper

BibTeX
@InProceedings{pmlr-v41-dutta15, title = {{Interactive Visual Big Data Analytics for Large Area Farm Biosecurity Monitoring: i-EKbase System}}, author = {Dutta, Ritaban and Mueller, Heiko and Smith, Daniel and Das, Aruneema and Aryal, Jagannath}, booktitle = {Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications}, pages = {9--18}, year = {2015}, editor = {Fan, Wei and Bifet, Albert and Yang, Qiang and Yu, Philip S.}, volume = {41}, series = {Proceedings of Machine Learning Research}, month = {10 Aug}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v41/dutta15.pdf}, url = {https://proceedings.mlr.press/v41/dutta15.html}, abstract = {In this industrial application paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. We propose a cloud computing based intelligent big data analysis and interactive visual analytics platform to predict farm hot spots with high probability of potential biosecurity threats and early monitoring system aiming to save the farm from significant economic damage. } }
Endnote
%0 Conference Paper %T Interactive Visual Big Data Analytics for Large Area Farm Biosecurity Monitoring: i-EKbase System %A Ritaban Dutta %A Heiko Mueller %A Daniel Smith %A Aruneema Das %A Jagannath Aryal %B Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications %C Proceedings of Machine Learning Research %D 2015 %E Wei Fan %E Albert Bifet %E Qiang Yang %E Philip S. Yu %F pmlr-v41-dutta15 %I PMLR %P 9--18 %U https://proceedings.mlr.press/v41/dutta15.html %V 41 %X In this industrial application paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. We propose a cloud computing based intelligent big data analysis and interactive visual analytics platform to predict farm hot spots with high probability of potential biosecurity threats and early monitoring system aiming to save the farm from significant economic damage.
RIS
TY - CPAPER TI - Interactive Visual Big Data Analytics for Large Area Farm Biosecurity Monitoring: i-EKbase System AU - Ritaban Dutta AU - Heiko Mueller AU - Daniel Smith AU - Aruneema Das AU - Jagannath Aryal BT - Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications DA - 2015/08/31 ED - Wei Fan ED - Albert Bifet ED - Qiang Yang ED - Philip S. Yu ID - pmlr-v41-dutta15 PB - PMLR DP - Proceedings of Machine Learning Research VL - 41 SP - 9 EP - 18 L1 - http://proceedings.mlr.press/v41/dutta15.pdf UR - https://proceedings.mlr.press/v41/dutta15.html AB - In this industrial application paper a novel application of salad leaf disease detection has been developed using a combination of big data analytics and on field multi-dimensional sensing. We propose a cloud computing based intelligent big data analysis and interactive visual analytics platform to predict farm hot spots with high probability of potential biosecurity threats and early monitoring system aiming to save the farm from significant economic damage. ER -
APA
Dutta, R., Mueller, H., Smith, D., Das, A. & Aryal, J.. (2015). Interactive Visual Big Data Analytics for Large Area Farm Biosecurity Monitoring: i-EKbase System. Proceedings of the 4th International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications, in Proceedings of Machine Learning Research 41:9-18 Available from https://proceedings.mlr.press/v41/dutta15.html.

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