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Researchers at the University of California, Riverside have devised a method for classifying the different species of insects with up to 99 percent accuracy. 

Researchers said the development could help farmers protect their crops from insect damage and also limit the spread of insect-borne diseases like malaria and Dengue fever.

Researchers have build an inexpensive wireless bug sensor that can track many insect flight behavior patterns generating much larger amounts of data that be used as an input in the classification algorithm. 

"We set out not knowing what was possible," said Eamonn Keogh, a computer science professor at UC Riverside's Bourns College of Engineering, in the press release. "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 sensor consisted of a phototransistor array which is connected to an electronic board and a laser pointing at the phototransistor array.

When the insect passes across the laser beam, its wings partially block the light, causing a small light fluctuation. The fluctuations are captured by the phototransistor array as changes in current, the signal is then filtered and amplified by the custom designed electronic board.  The output of the electronic board is fed into a digital sound recorder and recorded as an MP3 and downloaded to a computer, the release explained. 

The research was supported by the Vodafone Americas Foundation, the Bill and Melinda Gates Foundation and São Paulo Research Foundation (FAPESP).

The research findings will be published in the upcoming issue of the Journal of Insect Behavior.