2011 SIGKDDDemoSensorsandSoftwaretoA

• (Batista et al., 2011) ⇒ Gustavo E. Batista, Eamonn J. Keogh, Agenor Mafra-Neto, and Edgar Rowton. (2011). “SIGKDD Demo: Sensors and Software to Allow Computational Entomology, An Emerging Application of Data Mining.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011). doi:10.1145/2020408.2020530

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Cited By

• http://scholar.google.com/scholar?q=%22SIGKDD+demo%3A+sensors+and+software+to+allow+computational+entomology%2C+an+emerging+application+of+data+mining%22+2011
• http://portal.acm.org/citation.cfm?doid=2020408.2020530&preflayout=flat#citedby

Quotes

Abstract

The history of humankind is intimately connected to insects. Insect borne diseases kill a million people and destroy tens of billions of dollars worth of crops annually. However, at the same time, beneficial insects pollinate the majority of crop species, and it has been estimated that approximately one third of all food consumed by humans is directly pollinated by bees alone. Given the importance of insects in human affairs, it is somewhat surprising that computer science has not had a larger impact in entomology. We believe that recent advances in sensor technology are beginning change this, and a new field of Computational Entomology will emerge. We will demonstrate an inexpensive sensor that allows us to capture data from flying insects, and the software that allows us to analyze the data. Moreover, we will distribute both the sensors and software for free, to parties willing to take part in a crowdsourcing project on insect classification.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 SIGKDDDemoSensorsandSoftwaretoA	Eamonn Keogh Gustavo E. Batista Agenor Mafra-Neto Edgar Rowton			SIGKDD Demo: Sensors and Software to Allow Computational Entomology, An Emerging Application of Data Mining				10.1145/2020408.2020530