RIVERSIDE, Calif. (http://www.ucr.edu) University of California, Riverside researchers have created a method that can classify different species of insects with up to 99 percent accuracy, a development that could help farmers protect their crops from insect damage and limit the spread of insect-borne diseases, such as malaria and Dengue fever.
Over the past 60 years, insect classification research has been limited by factors including an overreliance on acoustic sensing devices, a heavy focus on wingbeat frequency and limited data.
The UC Riverside researchers overcame those limitations by building an inexpensive wireless bug sensor that can track many insect flight behavior patterns and generate much larger amounts of data that can then be incorporated into classification algorithms.
In about three years, by having dozens of sensors running in parallel 24 hours a day, the UC Riverside researchers have collected tens of millions of data points, more than all previous work in this field combined.
"We set out not knowing what was possible," said Eamonn Keogh, a computer science professor at UC Riverside's Bourns College of Engineering. "Now, the problem is essentially solved. We have created insect classification tools that can outperform the world's top entomologists in a fraction of the time."
The research findings are under review for publication in an upcoming issue of the Journal of Insect Behavior. Keogh's co-authors are: Yanping Chen, a computer science graduate student at UC Riverside (the lead author); Adena Why, an entomology graduate student at UC Riverside; Gustavo Batista, of the University of Sao Paulo in Brazil; and Agenor Mafra-Neto, of ISCA Technologies in Riverside.
Filled with tables, chairs and computers, Keogh's lab at the University of California, Riverside Bourns College of Engineering looks like many computer science labs.<
|Contact: Sean Nealon|
University of California - Riverside